CN112951373A

CN112951373A - Food material recommendation method and device, intelligent refrigerator and intelligent terminal

Info

Publication number: CN112951373A
Application number: CN202110151888.9A
Authority: CN
Inventors: 孟卫明
Original assignee: Hisense Group Holding Co Ltd
Current assignee: Hisense Group Holding Co Ltd
Priority date: 2021-02-03
Filing date: 2021-02-03
Publication date: 2021-06-11

Abstract

The invention discloses a food material recommending method, a device, an intelligent refrigerator and an intelligent terminal, wherein the food material recommending device comprises a processor and a data acquiring unit; the data acquisition unit is configured to: acquiring basic information of a user and a pre-constructed knowledge graph of healthy food materials; wherein the basic information of the user comprises the health state information of the user and the personal information of the user; the processor is configured to: determining recommended food materials based on basic information of a user and a pre-constructed healthy food material knowledge graph, wherein the healthy food material knowledge graph is used for representing association relations between various food materials and diseases and matching relations between various food materials and personal information; and screening the recommended food materials by using the user portrait data to determine the target recommended food materials. The food material recommendation is more rapid and convenient, and the food material recommendation accuracy is improved.

Description

Food material recommendation method and device, intelligent refrigerator and intelligent terminal

Technical Field

The invention relates to the technical field of intelligent home furnishing, in particular to a food material recommending method, food material recommending equipment, an intelligent refrigerator and an intelligent terminal.

Background

With the improvement of economic level and material level, people pay more and more attention to the physical health of themselves and family, and the requirement and the taste of consumers on diet are continuously increased. In modern life, people who want to regulate body states by improving food materials have higher requirements on what people eat and how people eat due to reasons of accelerated life pace, high life pressure and the like.

At present, aiming at the subdivision field of healthy diet recommendation, the method still stays in the channels of books, hospital food therapy schemes, health-care dieticians and the like to obtain healthy diet suggestions. However, in these times, book recommendations are generally less accurate. Hospital diet therapy programs are usually highly targeted, and when the physical health of a user changes, the previously specified diet therapy programs are not applicable, so that new diet therapy programs are prepared again.

Disclosure of Invention

The invention provides a food material recommending method, food material recommending equipment, an intelligent refrigerator and an intelligent terminal, which can conveniently and quickly recommend suitable food materials to a user while improving the food material recommending precision.

According to a first aspect of exemplary embodiments, there is provided a food material recommendation method, the method comprising:

acquiring basic information of a user, wherein the basic information of the user comprises health state information of the user and personal information of the user;

determining recommended food materials based on basic information of a user and a pre-constructed healthy food material knowledge graph, wherein the healthy food material knowledge graph is used for representing association relations between various food materials and diseases and matching relations between various food materials and personal information;

and screening the recommended food materials by using the user portrait data to determine the target recommended food materials.

According to the embodiment of the application, the food materials are recommended to the user through the food material recommending device, the personal information and the health state information of the user are comprehensively considered, and then the recommended food materials matched with the user can be determined through the incidence relation between various food materials and diseases represented by the health food material knowledge graph constructed in advance and the matching relation between various food materials and the personal information, so that the user can obtain the recommended food materials more conveniently and quickly, the obtained recommended food materials are more consistent with the user condition, and the recommendation is more accurate; meanwhile, recommended food materials are further screened by combining the user portrait data, so that the information of user preference or habit and the like is comprehensively considered, and the accuracy of food material recommendation is further improved.

In some exemplary embodiments, determining the recommended food material based on the basic information of the user and the pre-constructed knowledge graph of the healthy food material comprises:

if the health state information of the user represents that the user is sick, determining the sick type of the user;

determining food materials matched with the diseased type of the user as first alternative food materials based on the diseased type of the user and the incidence relation between various food materials and diseases represented by the healthy food material knowledge graph;

according to the matching relation between various food materials represented by the healthy food material knowledge graph and the personal information, first alternative food materials which are not matched with the personal information of the user in the first alternative food materials are removed, and the recommended food materials are determined.

In the embodiment, when a user is ill, if there are food materials which are not suitable for the ill-suffered user to eat among the food materials recommended to the user, the physical health of the user may be seriously affected. Therefore, when the user is determined to be ill, the food materials are preferentially recommended according to the ill type of the user, so that the food materials influencing the body health of the user can be prevented from being recommended; and then, combining the personal information of the user, removing the food materials which are not matched with the personal information of the user, and obtaining the recommended food materials.

In some exemplary embodiments, the pre-constructed healthy food material knowledge graph is also used to characterize the gram relationships between various types of food materials;

determining food materials matched with the diseased types of the users as first alternative food materials based on the diseased types of the users and the incidence relations between various food materials and diseases represented by the pre-constructed knowledge graph of the healthy food materials, wherein the method comprises the following steps:

determining the taboo type of the existing food material according to the illness type and the association relation of the user; the existing food materials are determined according to food material purchase records of users and/or food materials determined according to food material storage information of food material storage equipment;

if the existing food materials are determined to have no taboo relationship with the diseased types of the users, determining the restriction relationship of each food material in the existing food materials according to the restriction relationship;

and determining a first alternative food material according to the taboo type of the existing food materials and the gram relationship of each food material in the existing food materials.

According to the embodiment, when the user is ill, the taboo relationship between the ill disease of the user and the existing food materials is determined, and when the taboo relationship does not exist, the restriction relationship between the existing food materials is determined, so that the determined first alternative food materials realize the subdivision of the food material recommendation when the user is ill, and the recommendation is more accurate.

determining recommended food materials based on basic information of users and a pre-constructed knowledge graph of healthy food materials, wherein the method comprises the following steps:

if the health condition information represents that the user is not sick, determining a second alternative food material according to the personal information of the user and the matching relation between various food materials represented by the health food material knowledge graph and the personal information;

determining the restriction relation of each food material in the existing food materials and the food materials restricted by each food material in the existing food materials according to the restriction relation of each food material represented by the healthy food material knowledge graph; the existing food materials are determined according to the food material purchase records of the user and/or the food materials determined according to the food material storage information of the food material storage equipment;

and determining the recommended food materials from the second alternative food materials according to the gram relationship among the existing food materials and the food which is gram with each food material in the existing food materials.

In the embodiment, when the user is not ill, in the recommendation process, the personal information of the user is directly applied to match with the knowledge graph of the healthy food materials without considering the body health state information of the user, so that the second alternative food materials are determined, and then the recommended food materials are further screened from the second alternative food materials according to the gram relationship of the existing food materials. Accurate recommendation according to the personal information of the user is achieved.

determining a third alternative food material according to the personal information of the user and the matching relation between various food materials represented by the health food material knowledge graph and the personal information;

determining a fourth alternative food material according to the health state information of the user and the incidence relation between various food materials and diseases represented by the health food material knowledge graph;

if the existing food materials comprise common food materials in the third alternative food material and the fourth alternative food material, determining the common food materials as recommended food materials; the existing food materials are determined according to the food material purchase records of the user and/or the food materials determined according to the food material storage information of the food material storage equipment;

and if the existing food materials do not comprise the shared food materials in the third alternative food material and the fourth alternative food material, determining recommended food materials in the existing food materials according to the knowledge graph of the healthy food materials and the basic information of the user.

According to the embodiment, whether the user is ill or not is not required to be determined in advance, recommendation is performed according to the personal information of the user and the health state information of the user, and then common food materials in the recommendation of the user and the health state information of the user are determined, so that primary and secondary recommendations are not performed, and the recommendation is more comprehensive; in addition, the existing food materials are considered, and the recommendation is carried out by combining the relation between the existing food materials and the public food materials, so that the adaptability of the recommendation of the food materials is stronger, and the accuracy is higher.

In some exemplary embodiments, the user profile data includes user preference information determined by obtaining a food material purchase record of the user;

screening recommended food materials by using user portrait data, and determining target recommended food materials, wherein the method comprises the following steps:

and sorting the recommended food materials according to the user preference information, and determining a preset number of recommended food materials as target recommended food materials.

According to the embodiment, the recommended food materials are further screened through the user preference information, so that the recommended food materials are more accurate, and the satisfaction degree of the user is higher.

In some exemplary embodiments, after determining the recommended food material, the method further comprises:

displaying the target recommended food material on a food material recommendation page;

acquiring editing information of a user through editing operation of the user on a recommended page;

the user portrait data is updated based on the edit information.

According to the embodiment, the recommended food materials are displayed, so that the recommended food materials are recommended to the user more intuitively; the user portrait data are updated in time, so that the recommended food materials are updated along with the updating of the user portrait data, and the recommendation is more accurate.

According to a second aspect of the exemplary embodiments, there is provided a food material recommendation apparatus comprising a processor and a data acquisition unit, wherein:

the data acquisition unit is configured to:

acquiring basic information of a user and a pre-constructed knowledge graph of healthy food materials; wherein the basic information of the user comprises the health state information of the user and the personal information of the user;

the processor is configured to:

In some exemplary embodiments, the processor is configured to:

In some exemplary embodiments, when the pre-constructed healthy food material knowledge graph is also used to characterize the gram relationships between various types of food materials;

the processor is configured to:

and determining the recommended food materials from the second alternative food materials according to the gram relationship among the existing food materials and the food materials which are gram with each food material in the existing food materials.

In some exemplary embodiments, the processor is configured to:

In some exemplary embodiments, the user profile data includes user preference information determined by obtaining a food material purchase record of the user, the processor is configured to:

In some exemplary embodiments, the processor is further configured to:

after the recommended food materials are determined, displaying the target recommended food materials on a food material recommendation page;

the user portrait data is updated based on the edit information.

According to a third aspect of the exemplary embodiments, there is provided a food material recommending apparatus including:

the system comprises an acquisition module, a management module and a management module, wherein the acquisition module is used for acquiring basic information of a user, and the basic information of the user comprises health state information of the user and personal information of the user;

the determining module is used for determining recommended food materials based on the basic information of the user and a pre-constructed healthy food material knowledge graph, wherein the healthy food material knowledge graph is used for representing the association relation between various food materials and diseases and the matching relation between various food materials and personal information;

and the screening module is used for screening the recommended food materials by using the user portrait data and determining the target recommended food materials.

In some exemplary embodiments, the determining module is specifically configured to:

In some exemplary embodiments, the pre-constructed healthy food material knowledge graph is also used to characterize the gram relationships between various types of food materials; the determination module is specifically configured to:

In some exemplary embodiments, the user profile data includes user preference information determined by obtaining a food material purchase record of the user; the screening module is specifically configured to:

In some exemplary embodiments, the display module is further configured to:

the user portrait data is updated based on the edit information.

According to a fourth aspect of the exemplary embodiments, there is provided an intelligent refrigerator including an identification unit, a display screen, and a processor:

the identification unit is configured to:

determining the existing food materials by identifying the obtained pictures of the existing food materials;

the processor is configured to:

determining recommended food materials based on the basic information of the user and a pre-constructed healthy food material knowledge graph, wherein the healthy food material knowledge graph is used for representing the association relation between various food materials and diseases and the matching relation between various food materials and personal information;

screening the recommended food materials by using user portrait data based on the existing food materials to determine target recommended food materials;

the display screen is further configured to:

and displaying the target recommended food material through characters and/or pictures.

According to a fifth aspect of the exemplary embodiments, there is provided a smart terminal including a touch screen and a processor:

the touch screen is configured to:

responding to the food material purchasing operation of a user, and generating a food material purchasing record according to the food material purchasing operation;

the processor is configured to:

determining the existing food materials according to the food material purchase records;

the processor is configured to:

the touch screen is further configured to:

According to a sixth aspect of the exemplary embodiments, there is provided a computer storage medium having stored therein computer program instructions which, when run on a computer, cause the computer to execute the food material recommendation method according to the first aspect.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.

Fig. 1 is a block diagram of a hardware configuration of a terminal according to an embodiment of the present disclosure;

fig. 2 is a block diagram of a software structure of a terminal according to an embodiment of the present disclosure;

fig. 3 is a schematic diagram of a user interface on a terminal according to an embodiment of the present disclosure;

fig. 4 is a flowchart of a food material recommendation method according to an embodiment of the present application;

FIG. 5 is a schematic diagram of a multi-level classification presentation constructed in a atlas provided by an embodiment of the present application;

fig. 6 is a schematic view of a relationship between diseases and primary food materials provided in the embodiment of the present application;

fig. 7 is a schematic diagram illustrating a "taboo" relationship between a disease and a secondary food material according to an embodiment of the present disclosure;

fig. 8 is a schematic view of a relationship between diseases and secondary food materials provided in the embodiment of the present application;

fig. 9 is a schematic view illustrating a genetic relationship between food materials according to an embodiment of the present application;

fig. 10 is a schematic view of a restriction relationship between food materials according to an embodiment of the present application;

fig. 11 is a schematic view illustrating a relationship between occupation and food materials according to an embodiment of the present application;

fig. 12 is a schematic view illustrating a relationship between age and food material according to an embodiment of the present disclosure;

fig. 13 is a schematic view illustrating a relationship between gender and food materials according to an embodiment of the present disclosure;

fig. 14 is a schematic view of a knowledge graph of a healthy food material provided in an embodiment of the present application;

fig. 15 is a display page of a list of edible material suitable for eating according to the embodiment of the present application;

fig. 16 is a display page of a list of dietetic food materials according to an embodiment of the present application;

FIG. 17 is a display page of a reminder for a meal provided in an embodiment of the present application;

fig. 18 is a schematic structural diagram of an intelligent refrigerator provided in an embodiment of the present application;

fig. 19 is a schematic structural diagram of another intelligent refrigerator provided in an embodiment of the present application;

fig. 20 is a schematic structural diagram of an intelligent terminal according to an embodiment of the present application;

fig. 21 is a schematic structural diagram of a food material recommending apparatus according to an embodiment of the present application;

fig. 22 is a schematic structural diagram of a food material recommending apparatus according to an embodiment of the present application.

Detailed Description

The technical solution in the embodiments of the present application will be described in detail and removed with reference to the accompanying drawings. In the description of the embodiments herein, "/" means "or" unless otherwise specified, for example, a/B may mean a or B; "and/or" in the text is only an association relationship describing an associated object, and means that three relationships may exist, for example, a and/or B may mean: three cases of a alone, a and B both, and B alone exist, and in addition, "a plurality" means two or more than two in the description of the embodiments of the present application.

In the following, the terms "first", "second" are used for descriptive purposes only and are not to be understood as implying or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature, and in the description of embodiments of the application, unless stated otherwise, "plurality" means two or more.

The following explains the terms applied in the embodiments of the present application:

1. knowledge graph: the knowledge domain visualization or knowledge domain mapping map is a series of different graphs for displaying the relationship between the knowledge development process and the structure, and the visualization technology is used for describing knowledge resources and carriers thereof, mining, analyzing, constructing, drawing and displaying knowledge and the mutual relation between the knowledge resources and the carriers. The knowledge graph is a modern theory which achieves the aim of multi-discipline fusion by combining theories and methods of applying subjects such as mathematics, graphics, information visualization technology, information science and the like with methods such as metrology introduction analysis, co-occurrence analysis and the like and utilizing a visualized graph to vividly display the core structure, development history, frontier field and overall knowledge framework of the subjects.

In the embodiment of the application, the healthy food material knowledge graph is visually displayed by including relations or affiliations among food materials, generating and restraining relations among food materials, association relations between various food materials and diseases, matching relations between various food materials and personal information, and the like.

2. Generation and restriction of phase: dialectical relations among general substances, wherein the generation of the food materials shows that the two food materials mutually promote absorption or are beneficial to human bodies when being eaten at the same time; the restriction between the food materials means that the two food materials are mutually restrained and absorbed or the food materials are harmful to human bodies when being eaten at the same time.

3. The relationship between them is contraindicated: the contraindication relationship generally refers to the relationship between diseases and food materials, and a food material is good for a disease if the food material is good for the disease; a food material is contraindicated for each disease if it is bad for that disease.

4. The affiliation and inclusion relations among the food materials are as follows:

each food material has three-level classification attributes, such as "wonton skin" belonging to "wheat", and "wheat" belonging to "cereal product". The first-level food material classification of cereal and products and the second-level food material classification of wheat are in inclusion relation, and other second-level food material classifications are provided under the cereal and products. The secondary food material classification "wheat" is related to the food material "wonton wrappers", and similarly, many other food materials exist under the "wheat".

The application scenario described in the embodiment of the present invention is for more clearly illustrating the technical solution of the embodiment of the present invention, and does not form a limitation on the technical solution provided in the embodiment of the present invention, and it can be known by a person skilled in the art that with the occurrence of a new application scenario, the technical solution provided in the embodiment of the present invention is also applicable to similar technical problems.

With the improvement of economic level and material level, people pay more and more attention to the physical health of themselves and family, and the requirement and the taste of consumers on diet are continuously increased. In modern life, due to the reasons of accelerated pace of life, high pressure of life and the like, more and more people want to adjust the state of the people through food materials, and higher requirements are placed on what people eat and how people eat.

At present, aiming at the subdivision field of healthy diet recommendation, the method still stays in the channels of books, hospital food therapy schemes, health-care dieticians and the like to obtain healthy diet suggestions. However, in these methods, the user cannot acquire recommended food materials suitable for the user at any time and any place.

In view of this, the embodiment of the application provides a food material recommendation method and device, the food material recommendation device may be a smart phone or a smart television, or may be an intelligent refrigerator, and as long as the food material recommendation method in the embodiment of the application is integrated, after food material recommendation operation of a user is obtained, information such as occupation, age, gender, and physical health state information of the user is obtained through a user basic information base, weather season information of the location of the user is requested from a weather consultation website, healthy food material recommendation is obtained through a healthy food material knowledge graph, and then healthy food material recommendation is ranked by combining with a user graph base, so that healthy food material recommendation conforming to preferences of the user is obtained. Therefore, the user can conveniently and quickly determine the food materials suitable for the user through the mobile phone or the refrigerator at home without turning over books or using a hospital.

Fig. 1 shows a schematic structural diagram of a terminal 100.

The following describes an embodiment specifically by taking the terminal 100 as an example. It should be understood that the terminal 100 shown in fig. 1 is merely an example, and that the terminal 100 may have more or fewer components than shown in fig. 1, may combine two or more components, or may have a different configuration of components. The various components shown in the figures may be implemented in hardware, software, or a combination of hardware and software, including one or more signal processing and/or application specific integrated circuits.

A block diagram of a hardware configuration of the terminal 100 according to an exemplary embodiment is exemplarily shown in fig. 1. As shown in fig. 1, the terminal 100 includes: a Radio Frequency (RF) circuit 110, a memory 120, a display unit 130, a camera 140, a sensor 150, an audio circuit 160, a Wireless Fidelity (Wi-Fi) module 170, a processor 180, a bluetooth module 181, and a power supply 190.

The RF circuit 110 may be used for receiving and transmitting signals during information transmission and reception or during a call, and may receive downlink data of a base station and then send the downlink data to the processor 180 for processing; the uplink data may be transmitted to the base station. Typically, the RF circuitry includes, but is not limited to, an antenna, at least one amplifier, a transceiver, a coupler, a low noise amplifier, a duplexer, and the like.

The memory 120 may be used to store software programs and data. The processor 180 performs various functions of the terminal 100 and data processing by executing software programs or data stored in the memory 120. The memory 120 may include high speed random access memory and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device. The memory 120 stores an operating system that enables the terminal 100 to operate. The memory 120 may store an operating system and various application programs, and may also store codes for performing the methods of the embodiments of the present application.

The display unit 130 may be used to receive input numeric or character information and generate signal input related to user settings and function control of the terminal 100, and particularly, the display unit 130 may include a touch screen 131 disposed on the front surface of the terminal 100 and may collect touch operations of a user thereon or nearby, such as clicking a button, dragging a scroll box, and the like.

The display unit 130 may also be used to display a Graphical User Interface (GUI) of information input by or provided to the user and various menus of the terminal 100. Specifically, the display unit 130 may include a display screen 132 disposed on the front surface of the terminal 100. The display screen 132 may be configured in the form of a liquid crystal display, a light emitting diode, or the like. The display unit 130 may be used to display various graphical user interfaces in the present application.

The touch screen 131 may cover the display screen 132, or the touch screen 131 and the display screen 132 may be integrated to implement the input and output functions of the terminal 100, and after the integration, the touch screen may be referred to as a touch display screen for short. In the present application, the display unit 130 may display the application programs and the corresponding operation steps.

The camera 140 may be used to capture still images or video. The object generates an optical image through the lens and projects the optical image to the photosensitive element. The photosensitive element may be a Charge Coupled Device (CCD) or a complementary metal-oxide-semiconductor (CMOS) phototransistor. The light sensing elements convert the light signals into electrical signals which are then passed to the processor 180 for conversion into digital image signals.

The terminal 100 may further comprise at least one sensor 150, such as an acceleration sensor 151, a distance sensor 152, a fingerprint sensor 153, a temperature sensor 154. The terminal 100 may also be configured with other sensors such as a gyroscope, barometer, hygrometer, thermometer, infrared sensor, light sensor, motion sensor, etc.

Audio circuitry 160, speaker 161, and microphone 162 may provide an audio interface between a user and terminal 100. The audio circuit 160 may transmit the electrical signal converted from the received audio data to the speaker 161, and convert the electrical signal into a sound signal for output by the speaker 161. The terminal 100 may also be provided with a volume button for adjusting the volume of the sound signal. On the other hand, the microphone 162 converts the collected sound signal into an electrical signal, converts the electrical signal into audio data after being received by the audio circuit 160, and outputs the audio data to the RF circuit 110 to be transmitted to, for example, another terminal or outputs the audio data to the memory 120 for further processing. In this application, the microphone 162 may capture the voice of the user.

Wi-Fi belongs to a short-distance wireless transmission technology, and the terminal 100 can help a user to send and receive e-mails, browse webpages, access streaming media, and the like through the Wi-Fi module 170, and provides wireless broadband internet access for the user.

The processor 180 is a control center of the terminal 100, connects various parts of the entire terminal using various interfaces and lines, and performs various functions of the terminal 100 and processes data by running or executing software programs stored in the memory 120 and calling data stored in the memory 120. In some embodiments, processor 180 may include one or more processing units; the processor 180 may also integrate an application processor, which mainly handles operating systems, user interfaces, applications, etc., and a baseband processor, which mainly handles wireless communications. It will be appreciated that the baseband processor described above may not be integrated into the processor 180. In the present application, the processor 180 may run an operating system, an application program, a user interface display, a touch response, and a processing method according to the embodiments of the present application. Further, the processor 180 is coupled with the display unit 130.

And the bluetooth module 181 is configured to perform information interaction with other bluetooth devices having a bluetooth module through a bluetooth protocol. For example, the terminal 100 may establish a bluetooth connection with a wearable electronic device (e.g., a smart watch) having a bluetooth module via the bluetooth module 181, so as to perform data interaction.

The terminal 100 also includes a power supply 190 (e.g., a battery) to power the various components. The power supply may be logically connected to the processor 180 through a power management system to manage charging, discharging, power consumption, etc. through the power management system. The terminal 100 may also be configured with power buttons for powering the terminal on and off, and locking the screen.

Fig. 2 is a block diagram of a software configuration of the terminal 100 according to the embodiment of the present invention.

The layered architecture divides the software into several layers, each layer having a clear role and division of labor. The layers communicate with each other through a software interface. In some embodiments, the Android system is divided into four layers, an application layer, an application framework layer, an Android runtime (Android runtime) and system library, and a kernel layer from top to bottom.

The application layer may include a series of application packages.

As shown in fig. 2, the application package may include applications such as camera, gallery, calendar, phone call, map, navigation, WLAN, bluetooth, music, video, short message, etc.

The application framework layer provides an Application Programming Interface (API) and a programming framework for the application program of the application layer. The application framework layer includes a number of predefined functions.

As shown in FIG. 2, the application framework layers may include a window manager, content provider, view system, phone manager, resource manager, notification manager, and the like.

The window manager is used for managing window programs. The window manager can obtain the size of the display screen, judge whether a status bar exists, lock the screen, intercept the screen and the like.

The content provider is used to store and retrieve data and make it accessible to applications. The data may include video, images, audio, calls made and received, browsing history and bookmarks, phone books, etc.

The view system includes visual controls such as controls to display text, controls to display pictures, and the like. The view system may be used to build applications. The display interface may be composed of one or more views. For example, the display interface including the short message notification icon may include a view for displaying text and a view for displaying pictures.

The phone manager is used to provide a communication function of the terminal 100. Such as management of call status (including on, off, etc.).

The resource manager provides various resources for the application, such as localized strings, icons, pictures, layout files, video files, and the like.

The notification manager enables the application to display notification information in the status bar, can be used to convey notification-type messages, can disappear automatically after a short dwell, and does not require user interaction. Such as a notification manager used to inform download completion, message alerts, etc. The notification manager may also be a notification that appears in the form of a chart or scroll bar text at the top status bar of the system, such as a notification of a background running application, or a notification that appears on the screen in the form of a dialog window. For example, text information is prompted in the status bar, a prompt tone is given, the terminal vibrates, an indicator light flashes, and the like.

The Android Runtime comprises a core library and a virtual machine. The Android runtime is responsible for scheduling and managing an Android system.

The core library comprises two parts: one part is a function which needs to be called by java language, and the other part is a core library of android.

The application layer and the application framework layer run in a virtual machine. And executing java files of the application program layer and the application program framework layer into a binary file by the virtual machine. The virtual machine is used for performing the functions of object life cycle management, stack management, thread management, safety and exception management, garbage collection and the like.

The system library may include a plurality of functional modules. For example: surface managers (surface managers), Media Libraries (Media Libraries), three-dimensional graphics processing Libraries (e.g., OpenGL ES), 2D graphics engines (e.g., SGL), and the like.

The surface manager is used to manage the display subsystem and provide fusion of 2D and 3D layers for multiple applications.

The media library supports a variety of commonly used audio, video format playback and recording, and still image files, among others. The media library may support a variety of audio-video encoding formats, such as MPEG4, h.264, MP3, AAC, AMR, JPG, PNG, and the like.

The three-dimensional graphic processing library is used for realizing three-dimensional graphic drawing, image rendering, synthesis, layer processing and the like.

The 2D graphics engine is a drawing engine for 2D drawing.

The kernel layer is a layer between hardware and software. The inner core layer at least comprises a display driver, a camera driver, an audio driver and a sensor driver.

The professional flow of the software and hardware of the terminal 100 is exemplarily described below in connection with capturing a photographing scene.

When the touch screen 131 receives a touch operation, a corresponding hardware interrupt is issued to the kernel layer. The kernel layer processes the touch operation into an original input event (including touch coordinates, a time stamp of the touch operation, and other information). The raw input events are stored at the kernel layer. And the application program framework layer acquires the original input event from the kernel layer and identifies the control corresponding to the input event. Taking the touch operation as a touch click operation, and taking a control corresponding to the click operation as a control of a camera application icon as an example, the camera application calls an interface of an application framework layer, starts the camera application, further starts a camera drive by calling a kernel layer, and captures a still image or a video through the camera 140.

The terminal 100 in the embodiment of the present application may be a mobile phone, a tablet computer, a wearable device, a notebook computer, a television, and the like.

Fig. 3 is a schematic diagram for illustrating a user interface on a terminal (e.g., terminal 100 of fig. 1). In some implementations, a user can open a corresponding application by touching an application icon on the user interface, or can open a corresponding folder by touching a folder icon on the user interface.

With respect to the above scenario, the following describes an embodiment of the present invention in further detail with reference to the drawings of the specification.

The following describes technical solutions of the embodiments of the present application with reference to various embodiments.

S401, acquiring basic information of a user, wherein the basic information of the user comprises health state information of the user and personal information of the user.

S402, determining recommended food materials based on the basic information of the user and a pre-constructed healthy food material knowledge graph, wherein the healthy food material knowledge graph is used for representing the association relation between various food materials and diseases and the matching relation between the various food materials and the personal information.

S403, screening the recommended food materials by using the user portrait data, and determining the target recommended food materials.

Referring to S401, in order to make the recommended food material better conform to the situation of the user, detailed information of the user needs to be collected, so that accurate recommendation can be made for each user. In the recommendation process, the applied information can be generally divided into two types, one type is personal information of the user, such as the age, the sex, the occupation and the like of the user, the other type is health state information of the user, such as whether the user is healthy or sick, and if the user is sick, the type of the disease of the user can be determined according to the health state information.

The basic information of the user is obtained, and the obtaining process can be realized by the following modes:

for example, when a user uses a food material recommendation service built in the current food material recommendation device, the user is required to perform information registration, and the user is required to fill in personal information during registration, so that the food material recommendation service can obtain the personal information of the user. The user can also be prompted to update information regularly, for example, if the occupation of the user changes, the occupation in the basic information of the user can be updated. In addition, the food material recommendation service can also be associated with the treatment records of the user, and the health state information of the user can be acquired in time after the treatment of the user is completed each time, or the health state information can be updated manually after the treatment of the user is completed each time. Therefore, the latest basic information of the user can be acquired in real time.

Referring to S402, after obtaining the basic information of the user, determining recommended food materials based on the basic information of the user and a pre-constructed knowledge graph of healthy food materials. In the process, a healthy food material knowledge graph is also acquired, the healthy food material knowledge graph is constructed in advance, and the construction process can be completed on current food material recommendation equipment, such as a smart phone or a smart refrigerator, but the smart phone or the smart refrigerator is required to have strong data processing capacity. In general, the building process may be completed on other terminals. The healthy food material knowledge graph is used for representing the association relation between various food materials and diseases and the matching relation between various food materials and personal information. In this way, according to the personal information of the user and the matching relationship, and the health state information of the user and the association relationship, the recommended food material corresponding to the personal information and the health state information of the user can be determined.

The process of constructing the knowledge graph of the healthy food material is described by a specific example as follows:

firstly, the topological structure and the relation of the knowledge graph of the healthy food materials are explained, food materials and classification entities are constructed, and a basic knowledge graph of the healthy food materials is formed, and referring to fig. 5, fig. 5 shows a schematic diagram of multi-level classification presentation constructed in the graph.

Referring to fig. 5, in the basic healthy food material knowledge graph, each food material, each secondary food material category, and each primary food material category are entities. Each type of entity has independent attributes. The entity attributes of the current primary and secondary food material classification are name and classification introduction; the attributes of the food materials are food material names, food material aliases, food material annotations, food material introductions and contents of nutrient elements such as proteins and vitamins.

Illustratively, each food material has a three-level classification attribute, such as "ravioli crust" to "wheat", and "wheat" to "cereal". The first-level food material classification of cereal and products and the second-level food material classification of wheat are in inclusion relation, and other second-level food material classifications are provided under the cereal and products. The secondary food material classification "wheat" is related to the food material "wonton wrappers", and similarly, many other food materials exist under the "wheat".

After the basic healthy food material knowledge graph is constructed according to the affiliation and inclusion relations of the food materials, the association of diseases and the food materials needs to be constructed, and the association can also be called a taboo relation, namely which food materials are not suitable for people suffering from which diseases and which food materials are beneficial for people suffering from which diseases. The contraindication relationship can be determined according to food material contraindication medical advice and food therapy schemes of various diseases, and not only contains the contraindication relationship between the diseases and a specific food material, but also has the contraindication relationship between the first-level food material classification and the second-level food material classification and the diseases, and the food materials belonging to the food material classification have the contraindication relationship between the classification and the diseases.

The relationship between disease and food material is described in the map as the relationship between disease entity and food material with the joints indicated by directional arrows.

Fig. 6 shows a schematic view of the "fit" relationship of a disease and a food material. Referring to fig. 6, the first food material classification "cereals and products" is preferably "liver cirrhosis". The relationship between the two is the attribute reason, and the current reason is that the food containing abundant zinc and magnesium is suitable for eating, which is helpful to enhance the liver function and resistance and increase the blood coagulation function. The source of each contraindicated relationship in the map may be years of clinical experience for the cooperative hospital practice.

Fig. 7 shows a schematic diagram of a disease and food material 'taboo' relationship. Referring to fig. 7, a map construction example of the porridge class which is a food grade food classification for diabetic patients.

Fig. 8 shows a schematic view of the "fit" relationship of another disease and food material. Referring to fig. 8, an example of the construction of a spectrum of a specific food material "chaotic skin" beneficial to the disease "bronchitis".

In the actual application process, the relationship between seasons and food material taboos can be constructed, for example, what types of food materials are suitable for eating in a certain season. The construction process refers to the construction process of the above-mentioned disease or personal information.

In addition, fig. 9 shows a schematic diagram of the generation relationship between food materials, fig. 10 shows a schematic diagram of the restriction relationship between food materials, and referring to fig. 9 and fig. 10, the restriction relationship between food materials is the restriction relationship between every two food materials, which can be described by the direct connection relationship between the food materials. In one specific example, the relationship between compatibility and compatibility has causal attributes, such as the relationship between buckwheat and rice has a "B group vitamin supplement".

In addition, the edibility of the food materials such as age, occupation and gender in the personal information is similar to the edibility construction of the diseased food materials, and the edibility relationship is constructed among the edibility, the first-level food material and the second-level food material by constructing each age group, each type of occupation and each gender. Fig. 11 shows a schematic diagram of the relationship between occupation and food material, referring to fig. 11, in this example, the programmer stares at more computer screen with eyes and eats more pork liver names; FIG. 12 is a schematic diagram showing the relationship between age and food material, and referring to FIG. 12, in this example, a red coat on the surface of peanut increases blood viscosity and increases the risk of thrombosis, so that people from 55 to 70 years of age should not eat more; fig. 13 shows a schematic diagram of the relationship between gender and food material, and referring to fig. 13, in this example, more apples eaten by women have a lubricating effect on the skin. It should be noted that fig. 6-13 only show one or more healthy food material knowledge maps selected, and in the practical application process, the healthy food material knowledge maps include a large number of taboos, inter-occurrence and inter-restriction relationships, and the like.

In summary, fig. 14 shows a schematic diagram of the health food material knowledge graph, and the schematic diagrams in fig. 6 to 13 are all partially shown in fig. 14, so that the visualization effect after the health food material knowledge graph is constructed is realized.

The following description is made for the recommendation process of food materials in different situations by using different examples:

in the first case, the health status information of the user characterizes the user as ill.

When the health state information of the user represents that the user is ill, determining the ill type of the user according to the health state information of the user, and determining the food material matched with the ill type of the user as a first alternative food material based on the ill type of the user and the incidence relation between various food materials and diseases represented by the healthy food material knowledge graph; and then according to the matching relation between various food materials represented by the healthy food material knowledge graph and the personal information, rejecting first alternative food materials which are not matched with the personal information of the user in the first alternative food materials, and determining recommended food materials.

For example, if the user suffers from diabetes and bronchitis, the diabetic should eat high fiber food according to the association (contraindication) between various food materials and diseases, such as: corn, wheat, cabbage, leek, legumes and peanuts; vegetables with low sugar content, such as: leek, pumpkin, wax gourd, pumpkin, etc.; porridge is not suitable for drinking, and wonton wrappers are suitable for people with bronchitis, so that the first alternative food materials can be corn, wheat, Chinese cabbage, Chinese chives and bean products, pumpkin, wax gourd and wonton wrappers. And if the current user is the old, peanuts which are not suitable for being eaten by the old frequently are removed according to the matching relation between various food materials represented by the healthy food material knowledge graph and personal information, because the blood viscosity is increased and the risk of suffering from thrombus is increased due to the red skin on the surface of the peanuts, the peanuts are not suitable for being eaten by the old. Thus, the food materials after the peanuts are removed are taken as recommended food materials.

The above example is that the food material recommendation is performed for the user according to the user basic information without considering the existing food material. In order to make the food material recommendation more intelligent and more in line with the actual situation of the user, the recommendation process of the food material by combining the existing food material is explained.

In this example, the determined food material is determined according to the food material purchase record of the user, and/or the existing food material is determined according to the food material storage information of the food material storage device; determining the taboo type of the existing food material according to the illness type and the association relation of the user; if the existing food materials are determined to have no taboo relationship with the diseased types of the users, determining the restriction relationship of each food material in the existing food materials according to the restriction relationship; and determining a first alternative food material according to the taboo type of the existing food materials and the gram relationship of each food material in the existing food materials.

Specifically, the food material recommending device is a mobile phone as an example, the food material storing device is a refrigerator as an example, the user accesses the food material purchasing interface through the mobile phone, the mobile phone obtains the food material purchasing record of the user, and the existing food material can be determined through the food material purchasing record and the food material taking record. In a specific example, the food material taking-out record may be that each time the user takes out a type of food material, the user marks a display page of the existing food material to update the existing food material.

In addition, the refrigerator can shoot the existing food materials through the built-in camera device to obtain pictures of the existing food materials, the pictures of the existing food materials can be used as food material storage information, the pictures are identified, and the existing food materials are determined. In an actual application process, the refrigerator may further include a touch screen, the touch screen responds to a food material purchasing operation of a user to generate a food material purchasing record, and the existing food material is determined by the manner of determining the existing food material through the mobile phone, which is described herein in detail. All the ways of determining the existing food materials can be applied to the embodiment of the application.

After the existing food materials are determined, the type of the taboo of the existing food materials is determined according to the disease type and the association relationship of the user, namely, the type suitable for the user is preferred and the type unsuitable for the user is taboo in the existing food materials. Determining the restriction relationship between any two types of food materials in the existing food materials according to the restriction relationship, and finally determining a first alternative food material by combining the food materials with the preference types in the existing food materials and the restriction relationship in the existing food materials. For example, the foods suitable for the types of food materials in existence are persimmon, spinach, egg and kelp, and if the persimmon and kelp are in a mutual restriction relationship, the kelp or persimmon is removed and used as the first candidate food material.

In a second case, the health status information of the user characterizes a situation in which the user is not ill.

If the health condition information of the user represents that the user is not sick, determining a second alternative food material according to the personal information of the user and the matching relation between various food materials represented by the health food material knowledge graph and the personal information; determining the restriction relation of each food material in the existing food materials and the food materials restricted by each food material in the existing food materials according to the restriction relation of each food material represented by the healthy food material knowledge graph; and determining the recommended food materials from the second alternative food materials according to the gram relationship among the existing food materials and the food which is gram with each food material in the existing food materials.

Specifically, if the user is not sick, the second alternative food materials are obtained through personal information matching, for example, the user is 35 years old, female and teacher, the second alternative food materials are oat, broccoli, pork liver, almond and salmon, and it is determined that each food material in the second alternative food materials does not have a mutual restriction relationship. In order to improve the food material recommendation, the food material which is not available for the user and is compatible with the existing food material is determined, so that the user is prompted not to buy the food material which is compatible with the existing food material. In this way, the recommended food material is determined by combining the restriction relationship between the existing food materials and the restriction food materials of other food materials between the existing food materials. In addition, when the recommended food materials are displayed, food materials which are similar to the existing food materials and are not available to the user at present can be displayed to the user, so that a reminding effect is achieved.

The two situations are divided according to whether the user is ill or not, and in the actual application process, the third alternative food material can be directly recommended according to the basic information of the user, namely, whether the user is ill or not, the third alternative food material is determined directly according to the personal information of the user and the matching relation between various food materials and the personal information; and determining a fourth alternative food material according to the health state information of the user and the incidence relation between various food materials and diseases.

Thus, if a common food material exists between the third alternative food material and the fourth alternative food material, the common food material can be taken as a recommended food material, and the common food material can be further screened to determine the recommended food material. For example, it is determined whether the common food material is included in the existing food materials, if so, the common food material is determined as a recommended food material, otherwise, the recommended food material is determined in the existing food materials according to the knowledge graph of the healthy food materials and the basic information of the user, and the determination method is as in the foregoing embodiment, which is not described herein again.

In addition, if a shared food material exists between the third alternative food material and the fourth alternative food material, the combination of the third alternative food material and the fourth alternative food material can be taken as the recommended food material after the shared food material is removed.

Additionally, if there is no common food material between the third alternative food material and the fourth alternative food material, the combination of the alternative food materials of the third alternative food material and the fourth food material can be taken as the recommended food material.

Referring to S403, since the recommended food material only considers whether the personal information of the user and the health status information of the user are met, the personal taste of the user is not considered. Therefore, in order to realize more accurate food material recommendation, the recommended food materials are screened by using the user portrait data, and the screened food materials are determined as the target recommended food materials.

The following describes the determination of user profile data in a particular embodiment:

specifically, the method can be used for evaluating the food material preference of the user by analyzing the purchasing behavior of the user, the clicking behavior on the food material purchasing page and the like. Taking a smart phone as an example, if a user places an order or browses on a food material purchase page, the purchase behavior of the user can be analyzed according to the purchase record and the browsing record of the user. Taking a large-screen intelligent refrigerator as an example, a user purchases or clicks on the large-screen intelligent refrigerator by operating a screen of the large-screen intelligent refrigerator. Each time the refrigerator is operated, a request is generated, an interface of the healthy food material recommending system is called, the system can be integrated in the refrigerator, and after the interface receives the request, relevant information of the request is recorded in a user behavior recording table of a user portrait library.

Therefore, the user image library stores records of food material purchased by the user, food material disliked feedback records of the user, food material stored and taken by the user in the refrigerator and the like, and user preference information obtained according to behavior analysis of the user. The user preference information needs to be obtained by reading the food material purchase record of the user by the healthy food material recommending service regularly and combining the purchase behavior analysis of similar users.

In one specific example, a cell phone, a smart refrigerator, and a smart speaker may be used to collect behavior information of a user. For example, the large screen of the intelligent Haixin refrigerator has a food material purchasing function, after the food material recommending service is carried out, clicking purchasing or clicking dislike operation is carried out at the large screen end of the refrigerator, after feedback is received, the information is fed back to the healthy food material recommending service, and the information is recorded in a user picture library. The food material identification function of the intelligent refrigerator with the WeChat can identify the food material access information of the user, and the partial data can be stored in the user portrait library. Interaction between the user and the intelligent sound box, such as ordering to purchase a certain food material by voice, inquiring detailed nutritional information of the certain food material and recording information of each food material in the menu recommendation to the user image library.

Illustratively, a scoring method is that a user clicks a recommended food material to count 1 point, and a user purchases a food material to count 2 points; the user stores the food material in the refrigerator for 1 point, and the user takes out the food material for 1 point. The score of the refrigerator food materials is used for distinguishing the scores of the food materials taken by the user frequently, and the scores are far higher than the scores of the food materials which are not taken by the user once the food materials are stored. The higher the frequency of food materials that a user frequently accesses, the higher the user's preference for the food material.

In order to more accurately determine the preference of the user, a time factor is introduced, so that the preference of the user and the change rule of the preference of the user along with time can be determined.

In a specific example, the user prefers a time decay score portrait, and the total score is finally obtained after adding a time decay function to the score of each behavior of the user. The food materials which are currently preferred by the user are recommended to the user for the user in consideration of the fact that the user preferences can change along with time for the clicking, purchasing and refrigerator storing behaviors of the user on certain food materials. In the user behavior record table of the user representation library, the form of the behavior record table of the user is as shown in table 1 below.

TABLE 1 user behavior record sheet

Time	Food material name	User ID	User behavior	User equipment	Remarks for note
						20201105	Tomato fruit	X	Purchasing	Mobile phone
20201106	Tomato fruit	X	Storage refrigerator	Intelligent refrigerator
						20201106	Mango (mango)	X	Dislike of	Mobile phone	Allergy (S)

For example, user X in table 1, tomato purchased on the mobile phone at 11 month 05, which was put in the refrigerator at 11 month 06, and user at 11 month 06 clicked dislike on mango material and checked the cause of allergy while browsing the material with the mobile phone.

The user behavior, as shown in table 1, and the final score of the user on the food material is table 2.

TABLE 2 user scoring table for food materials

User ID	Food material name	Total score
			X	Tomato fruit	2f(t0)+1f(t1)
X	Mango (mango)	-1f(t1)

Wherein f (t) is a time decay function. t is the time difference between the current time and the time at which the user generated the operation, in days. The time decay function is commonly used as linear decay, gaussian decay and exponential decay. The effect of the time decay function is illustrated by taking a linear decay function as an example. For example, the following linear decay function is taken as the time decay function of the embodiment of the present application:

if t < >50, then f (t) > 1-t/50; if t >50, f (t) is 0. Then the tomato score at 20201107 was 2 x (1-1/25) +1 x (1-1/50) ═ 2.9; the mango score at 20201107 was-1 x (1-1/50) ═ 0.98.

In this way, the sorting process based on the user portrait may be that, on the basis of the food materials recommended based on the healthy food material knowledge graph, the favorite scores of the users are added to each food material, and the recommendation results after sorting according to the scores are used as the target recommended food materials.

Still taking the apples and the mangos as examples, the food material recommendation and sorting based on the user portrait is a recommendation result obtained by adding a favorite score of the user to each food material and sorting according to the score on the basis of healthy food material recommendation based on the knowledge graph.

The specific implementation process may be to sort the scoring results by using a sorted function of Python. The args stores the calculated food material scores for the user in a data dictionary dit of Python, { 'tomato': 2.9, 'mango': 0.98 }. The food _ recom is a food material list to be sorted obtained through knowledge graph recommendation, and the data storage forms are { 'foodName': mango '}, {' foodName ': tomato' }. After sorting, the final result stored in result is { 'foodName': tomato '}, {' foodName ': mango' }.

The specific screening process may be to screen the recommended food materials with the scores larger than a preset score threshold value according to the scores, or to screen a preset number of recommended food materials. In this way, the target recommended food material which meets the individual preference of the user is found as the final recommended food material in the recommended food materials.

In order to make the technical solution of the embodiment of the present application clearer, a specific application example is used below to describe a flow of food material recommendation:

taking the food materials suitable for the user suffering from diseases as an example, for example, the user suffers from diabetes and hypertension, firstly positioning diabetes and hypertension entities in the knowledge map of the healthy food materials, then carrying out one-step reasoning according to the suitable relation constructed in the knowledge map by taking the two entities as starting points, if the reasoning result is a first-level food material classification, carrying out inclusion relation according to the classification of the food materials, and then carrying out two-step reasoning along the inclusion relation to obtain recommended food materials; and if the recommendation result is the secondary food material classification, verifying the inclusion relationship and reasoning to obtain the recommended food material according to the classification inclusion relationship of the food materials. And finally summarizing the food materials obtained by the one-step reasoning to obtain a list of the edible food materials to be recommended, and recording the list as a set A, wherein the edible food materials to be recommended are stored in the set A. In a specific example, fig. 15 shows a display page of a list of edible materials, and referring to fig. 15, the edible materials suitable for the user and the primary food material or the secondary food material to which the edible materials belong are also displayed, and in addition, the recommendation result further includes characteristics of the edible materials. For the convenience of the user, a purchase portal may also be presented for the user to purchase.

In the inference process, because of the inclusion relationship of the food materials, a food material beneficial to a certain disease may appear, and the food material in the list of the food materials to be recommended needs to be rejected as a contra-indicated food material when the food material appears in the contra-indicated list of another food material. And according to the method for obtaining the food materials to be recommended, obtaining a list of the food prohibited materials, and recording the list as a set B, wherein the food prohibited materials are stored in the set B. And (4) removing the food materials in the set B from the food materials in the set A to obtain a recommendation list based on the health food material knowledge graph, wherein the recommendation list stores the recommended food materials.

In a specific example, fig. 16 shows a display page of a list of food prohibited items, and referring to fig. 16, the food suitable for the user and the primary food or secondary food category to which the food is belonging are also displayed, and in addition, the recommendation result further includes the food material characteristics of the food suitable for eating. For the convenience of the user, a purchase entrance can be displayed, so that the user can purchase the product according to the condition of the user or the product can be purchased by family members.

In an actual application process, the intelligent refrigerator and the mobile phone can be linked to complete the food material recommendation process, and the food material recommendation process in the intelligent home scene is described as follows:

according to the food material storage list of the intelligent refrigerator, food materials owned by the current user are obtained, and food material use suggestion reminding is provided for the user by combining the food material compatibility and the user illness condition. For example, eggs, shredded cakes and fried dumplings are arranged in a refrigerator, a user suffers from diabetes and diarrhea, and a reminder of 'main and main should eat less fried eggs, shredded cakes and fried dumplings, and is not beneficial to diarrhea and diabetes' is generated for the user.

The generation process of the reminder is as follows:

1) the method comprises the steps that a small diet reminding request sent by an intelligent refrigerator is received by a mobile phone, and the request contains food material information contained in the refrigerator;

2) reading a user basic information base, acquiring basic information of a user, determining whether the user is ill, and if the user is ill, executing the step 3); if not, executing step 4);

3) and positioning the sick entity of the user in the knowledge graph and the useful food material entity in the refrigerator.

For each disease, the following were performed:

a. disease 1-benefit- > fridge food material;

b. disease 2-beneficial- > secondary food material classification-inclusion- > refrigerator food material;

c. disease 3-beneficial- > primary food material classification-inclusion- > secondary food material classification-inclusion- > refrigerator food material;

d. disease 4-contraindication- > fridge food;

e. disease 5-taboo- > secondary food material classification-inclusion- > refrigerator food material;

f. disease 6-taboo- > first-level food material classification-inclusion- > second-level food material classification-inclusion- > refrigerator food material;

the above 6 spectrum retrieval statements are executed. Wherein "-benefit- >", "-taboo- >", "-contain- >" means performing a directed path search according to a correspondence. If the search sentence contains a search sentence which is successfully executed, the return value is not null, the results of a plurality of diseases are integrated, and corresponding descriptions are generated according to the disease food material taboo; if the return values are all null, the food materials in the refrigerator and the user are sick and do not have a taboo relationship, and then the step 4) is executed;

4) positioning an entity of each food material in the knowledge graph, and executing the following steps aiming at the pairwise combination of the food materials of the refrigerator:

'refrigerator food material 1- [ fit ] -refrigerator food material 2'

h. "refrigerator food 1- [ Achek ] -refrigerator food 2"

And executing the two search sentences, and if the returned value part is not empty after the two search sentences are combined, the relationship that two foods are suitable or restrained exists. If a relationship of food material compatibility or restriction exists, for example, "buckwheat and pork liver in the master refrigerator cannot be eaten at the same time because the simultaneous eating affects the digestion and is easy to induce dysentery"; if no relation of gram exists, executing step 5);

5) if the user is ill, generating a food material beneficial or contraindicated reminder aiming at food materials which are not in the refrigerator according to ill information;

6) and if the user is not sick, randomly selecting a certain food material and generating a prompt aiming at the food material which is suitable or resistant. The generation method and the steps 3) and 4) do not limit refrigerator food materials in the path key points, and corresponding prompts of the user are fed back according to the finally returned food materials.

In one specific example, FIG. 17 shows a display page of a reminder for a meal, such as: diseases suffered by the user, diet cautions, the material characteristics of recommended materials, the material characteristics of contraindicated materials and the like.

As shown in fig. 18 and 19, based on the same inventive concept, an embodiment of the present invention provides an intelligent refrigerator including a display screen 182, a processor 183, and an identification unit 185.

The identification unit is configured to:

the identification unit may be a camera, which is disposed inside the intelligent refrigerator, as shown in fig. 18, and may be disposed at a corresponding inner position on the intelligent refrigerator door 184. The camera is not shown in fig. 18, only its position is illustrated.

The processor 183 is configured to:

the display screen 182 is further configured to:

For example, the user may click a touch button on the display screen 182 to view the target recommended food material, the existing food material, the user basic information, and the like, and may also update the user basic information.

As shown in fig. 20, based on the same inventive concept, the embodiment of the present invention provides an intelligent terminal including a processor 201 and a touch screen 202.

The touch screen 202 is configured to:

the processor 201 is configured to:

the touch screen 202 is further configured to:

For example, the intelligent terminal may refer to fig. 3 to show a terminal, where the food material recommendation service of the intelligent terminal may be shown to the user in the form of an icon, the name of the icon may be "food material recommendation", and the user may enter a food material recommendation page by clicking the icon.

As shown in fig. 21, based on the same inventive concept, an embodiment of the present invention provides a food material recommending apparatus, including an obtaining module 211, a determining module 212, and a screening module 213.

An obtaining module 211, configured to obtain basic information of a user, where the basic information of the user includes health status information of the user and personal information of the user;

the determining module 212 is configured to determine recommended food materials based on the basic information of the user and a pre-constructed healthy food material knowledge graph, where the healthy food material knowledge graph is used to represent association relations between various food materials and diseases and matching relations between various food materials and personal information;

and the screening module 213 is configured to screen the recommended food materials by using the user portrait data to determine the target recommended food materials.

In some exemplary embodiments, the determining module 212 is specifically configured to:

In some exemplary embodiments, the pre-constructed knowledge graph of healthy food materials is also used to characterize the taboo relationship of various food materials to diseases, and the gram relationship between various food materials; the determining module 212 is specifically configured to:

determining the taboo type of the existing food material according to the illness type and the taboo relationship of the user; the existing food materials are determined according to food material purchase records of users and/or food materials determined according to food material storage information of food material storage equipment;

In some exemplary embodiments, the pre-constructed knowledge graph of healthy food materials is also used to characterize the taboo relationship of various food materials to diseases, and the gram relationship between various food materials; the determining module 222 is specifically configured to:

In some exemplary embodiments, the screening module 213 is specifically configured to:

In some exemplary embodiments, the display module is further included for

the user portrait data is updated based on the edit information.

Since the apparatus is the apparatus in the method in the embodiment of the present invention, and the principle of the apparatus for solving the problem is similar to that of the method, the implementation of the apparatus may refer to the implementation of the method, and repeated details are not repeated.

As shown in fig. 22, based on the same inventive concept, an embodiment of the present invention provides a food material recommending apparatus, including: a processor 221 and a data acquisition unit 222.

The data acquisition unit 222 is configured to:

the processor 221 is configured to:

and screening the recommended food materials by using the user portrait data to determine the recommended food materials.

In some exemplary embodiments, the processor 221 is configured to:

In some exemplary embodiments, when the pre-constructed knowledge graph of healthy food materials is also used to characterize the taboo relationship of various food materials to diseases, and the gram relationship between various food materials;

the processor 221 is configured to:

In some exemplary embodiments, the processor 221 is configured to:

In some exemplary embodiments, when the user representation data includes user preference information determined by obtaining a food material purchase record of the user, the processor 221 is configured to:

and sorting the recommended food materials according to the user preference information, and determining a preset number of recommended food materials as the recommended food materials.

In some exemplary embodiments, the processor 221 is further configured to:

after the recommended food materials are determined, displaying the recommended food materials on a food material recommendation page;

the user portrait data is updated based on the edit information.

The embodiment of the invention also provides a computer storage medium, wherein computer program instructions are stored in the computer storage medium, and when the instructions run on a computer, the computer is enabled to execute the steps of the network distribution method of the electronic home equipment.

As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the spirit and scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is intended to include such modifications and variations as well.

Claims

1. A food material recommending apparatus is characterized by comprising a processor and a data obtaining unit;

the data acquisition unit is configured to:

acquiring basic information of a user and a pre-constructed knowledge graph of healthy food materials; wherein the basic information of the user comprises health status information of the user and personal information of the user;

the processor is configured to:

2. The food material recommendation device of claim 1, wherein the processor is configured to:

determining the food material matched with the diseased type of the user as a first alternative food material based on the diseased type of the user and the incidence relation between various food materials and diseases represented by the healthy food material knowledge graph;

according to the matching relation between various food materials and the personal information represented by the healthy food material knowledge graph, first alternative food materials which are not matched with the personal information of the user in the first alternative food materials are removed, and recommended food materials are determined.

3. The food material recommendation apparatus of claim 2, wherein when said pre-constructed healthy food material knowledge-graph is further used to characterize the inter-gram relationships between various types of food materials;

the processor is configured to:

determining the taboo type of the existing food material according to the illness type of the user and the incidence relation; the existing food materials are determined according to food material purchase records of users and/or food materials determined according to food material storage information of food material storage equipment;

if the existing food materials and the user diseased types are determined to have no taboo relationship, determining the restriction relationship of each food material in the existing food materials according to the restriction relationship;

and determining the first alternative food material according to the taboo type of the existing food materials and the gram relationship of each food material in the existing food materials.

4. The food material recommendation apparatus of claim 1, wherein when said pre-constructed healthy food material knowledge-graph is further used to characterize the inter-gram relationships between various types of food materials;

the processor is configured to:

if the health condition information represents that the user is not sick, determining a second alternative food material according to the personal information of the user and the matching relation between various food materials and the personal information represented by the health food material knowledge graph;

determining the restriction relation of each food material in the existing food materials and the food materials restriction with each food material in the existing food materials according to the restriction relation of each food material represented by the healthy food material knowledge graph; the existing food materials are determined according to food material purchase records of users and/or food materials determined according to food material storage information of food material storage equipment;

and determining recommended food materials in the second alternative food materials according to the gram relationship of each food material in the existing food materials and the food materials which are gram with each food material in the existing food materials.

5. The food material recommendation device of claim 1, wherein the processor is configured to:

determining a third alternative food material according to the personal information of the user and the matching relationship between various food materials represented by the healthy food material knowledge graph and the personal information;

if the existing food materials comprise common food materials in the third alternative food material and the fourth alternative food material, determining that the common food materials are recommended food materials; the existing food materials are determined according to food material purchase records of users and/or food materials determined according to food material storage information of food material storage equipment;

and if the existing food materials do not comprise the shared food materials in the third alternative food materials and the fourth alternative food materials, determining recommended food materials in the existing food materials according to the knowledge graph of the healthy food materials and the basic information of the user.

6. The food material recommendation device of any one of claims 1, wherein when the user profile data comprises user preference information determined by obtaining a food material purchase record of a user, the processor is configured to:

7. The food material recommendation device of any one of claims 1-6, wherein the processor is further configured to:

acquiring editing information of a user through the editing operation of the user on the recommended page;

and updating the user portrait data according to the editing information.

8. A food material recommendation method, characterized in that the method comprises:

9. The utility model provides an intelligence refrigerator which characterized in that, includes recognition element, display screen and treater:

the identification unit is configured to:

the processor is configured to:

the display screen is further configured to:

10. The intelligent terminal is characterized by comprising a touch screen and a processor:

the touch screen is configured to:

the processor is configured to:

the touch screen is further configured to: