CN111612580A - Method, device and equipment for recommending articles and storage medium - Google Patents
Method, device and equipment for recommending articles and storage medium Download PDFInfo
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Abstract
The embodiment of the invention discloses a method, a device, equipment and a storage medium for recommending articles. Wherein, the method comprises the following steps: determining an item configuration module and configuration parameters of the item configuration module; connecting modules in an item recommendation process according to configuration parameters of the item configuration module, wherein the item recommendation process comprises the item configuration module or comprises the item configuration module and a basic module; and recommending the article based on the connected article recommending process. According to the embodiment of the invention, the object recommending process is autonomously formed according to the needs of the user by determining the object configuration module and the configuration parameters, so that the object recommending flexibility and the recommending efficiency are improved.
Description
Technical Field
The embodiment of the invention relates to computer technology, in particular to an article recommendation method, device, equipment and storage medium.
Background
With the popularization of networks, users can check needed articles on line, so that the requirement on article recommendation is higher and higher, and the satisfaction degree of the users can be greatly reduced due to improper article recommendation.
The current article recommendation system comprises a plurality of processing nodes for recommending requests, and calling links connected among the nodes are fixed, so that calling links cannot be skipped or adjusted in sequence according to business needs, and the recommendation precision of each node cannot be confirmed. Therefore, the article recommending flexibility is low, and the recommended articles cannot accurately meet the user requirements.
Disclosure of Invention
The embodiment of the invention provides an article recommendation method, an article recommendation device, article recommendation equipment and a storage medium, which are used for modifying an article recommendation process according to requirements and improving the article recommendation flexibility.
In a first aspect, an embodiment of the present invention provides an item recommendation method, where the method includes:
determining an item configuration module and configuration parameters of the item configuration module;
connecting modules in an item recommendation process according to configuration parameters of the item configuration module, wherein the item recommendation process comprises the item configuration module or comprises the item configuration module and a basic module;
and recommending the article based on the connected article recommending process.
In a second aspect, an embodiment of the present invention further provides an article recommendation apparatus, where the apparatus includes:
the module and parameter determining module is used for determining an article configuration module and configuration parameters of the article configuration module;
the module connecting module is used for connecting modules in an item recommendation process according to configuration parameters of the item configuration module, wherein the item recommendation process comprises the item configuration module or comprises the item configuration module and a basic module;
and the article recommending module is used for recommending articles based on the connected article recommending process.
In a third aspect, an embodiment of the present invention further provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the processor implements the item recommendation method according to any embodiment of the present invention.
In a fourth aspect, embodiments of the present invention further provide a storage medium containing computer-executable instructions, which when executed by a computer processor, are configured to perform the item recommendation method according to any of the embodiments of the present invention.
According to the embodiment of the invention, the determined article configuration modules are connected by determining the article configuration modules and the configuration parameters, so that an article recommendation process meeting the requirements of users is formed, the problem that each module in the article recommendation process is fixed in the prior art is solved, the flexibility and the efficiency of article recommendation are improved, and the use experience of the users is improved.
Drawings
Fig. 1 is a schematic flow chart of an item recommendation method according to a first embodiment of the present invention;
FIG. 2 is a flowchart illustrating an item recommendation method according to a second embodiment of the present invention;
fig. 3 is a block diagram of an article recommendation device according to a third embodiment of the present invention;
fig. 4 is a schematic structural diagram of a computer device in the fourth embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
Example one
Fig. 1 is a flowchart illustrating an article recommendation method according to an embodiment of the present invention, where the embodiment is applicable to a case of recommending an article for a user, and the method may be executed by an article recommendation apparatus. As shown in fig. 1, the method specifically includes the following steps:
The article configuration module is a module for calculating article recommendation scores, and the server recommends articles for the user according to the recommendation scores. The configuration parameters of the item configuration module are parameters for adjusting the calculation results of the item configuration module and the recommendation results of the item recommendation process. In the item recommendation process, a plurality of item configuration modules may exist, a user selects a suitable item configuration module as required and confirms configuration parameters of the item configuration module, the configuration parameters may be manually input by the user, and the server receives user operation and determines the item configuration module and the configuration parameters.
In this embodiment, optionally, determining the article configuration module and the configuration parameters of the article configuration module includes: the item configuration module is used for acquiring an item recommendation process selected from the candidate configuration modules; and acquiring configuration parameters of the article configuration module input by a user.
Specifically, the candidate configuration modules are all article configuration modules to be confirmed, the server determines the article configuration modules from the candidate configuration modules, the user selects the article configuration modules required by the article recommendation process from the candidate configuration modules, and the server determines the article configuration modules according to the user operation. For example, the candidate configuration modules comprise an article recall module, a model calculation module and a filtering and pressing module, wherein the article recall module is used for calculating the recall score of an article according to the click rate and the click time of browsing the article by a user, and the recall score is high for the article with large click rate or the article with close click time to the current time; the model calculation module calculates the model score of the article according to a pre-trained neural network model, inputs user information into the neural network model, can obtain the model calculation score according to the user information, and when the user is female, the model score of the male article is smaller than that of the female article; the filtering and pressing module determines the pressing score of the article according to the inventory, the score and other attribute information of the article, wherein the article with less inventory or low score has high pressing score. The suppressing score may be a reduction to the item recommendation score, and the recall score and the model score are additions to the item recommendation score. Through different item recommendation modules, the recommendation scores of the items can be calculated in multiple angles. Or only one of the item recommendation modules can be selected, and the calculation precision of the item recommendation module or the influence degree of the item recommendation module on the recommendation score can be known. If the user only wants to recommend the article according to the recall score and the model score, the article recall module and the model calculation module can be selected as an article configuration module of the article recommendation process.
After the article configuration module is determined, the configuration parameters of the article configuration module input by the user can be obtained according to the user operation to determine the operation sequence of the article configuration module in the article recommendation process, and the recommendation score calculated by the article configuration module is adjusted according to the configuration parameters. For example, the fractional weight of each item configuration module may be adjusted. The article recommendation process is flexibly adjusted, and article recommendation efficiency is improved.
In this embodiment, optionally, the configuration parameters of the article configuration module include a connection relationship between different modules in the article recommendation process, and internal parameters of the article configuration module.
Specifically, the configuration parameters of the item configuration module may include connection relationships between different modules in the item recommendation process. The connection relationship between different modules in the item recommendation process means that a plurality of item configuration modules may exist in the item recommendation process, and different modules may be connected in different connection orders. For example, the connection sequence of the article configuration module can be "article recall module-model calculation module-filter pressing module", and also can be "article recall module-filter pressing module-model calculation module". By obtaining the configuration parameters, the connection order of the article configuration modules can be determined, and the article recommendation processes composed of the article configuration modules with different connection orders may result in different final recommendation scores.
The configuration parameters of the item configuration module may further include internal parameters of the item configuration module, where the internal parameters are parameters relating to calculation results of each item configuration module, for example, in the filtering and suppressing module, if the suppressing score is calculated for an item whose stock quantity is lower than the stock threshold, the parameters of the stock threshold may be changed, and the finally recommended item may be affected.
In this embodiment, optionally, before the obtaining of the item configuration module of the item recommendation process selected from the candidate configuration modules, the method further includes: and adding the acquired new configuration module into the candidate configuration module.
In particular, the candidate configuration modules may be updated, e.g., candidate configuration modules may be added, modified, or deleted. And if the new configuration module needs to be added, the server acquires the new configuration module input by the user and adds the new configuration module to the candidate configuration module, so that the user can conveniently select the article configuration module from the updated candidate configuration module. The candidate configuration module is updated, the item recommendation process meets the item recommendation requirement of the user, and the flexibility of the item recommendation process is improved.
And 120, connecting modules in an item recommendation process according to configuration parameters of the item configuration module, wherein the item recommendation process comprises an item configuration module or comprises the item configuration module and a basic module.
After the article configuration module and the configuration parameters are determined, updating and confirming the article configuration module according to internal parameters of the article configuration module in the configuration parameters, and connecting the article configuration module according to the connection relation between different modules in the configuration parameters to generate an article recommendation process. The item recommendation process can be composed of an item configuration module, and also can be composed of an item configuration module and a basic module. The basic module may be a fixed module in the item recommendation process, for example, it may be a ranking module, and if the determined item configuration module is an item recall module and a model calculation module, the item recommendation process may be "item recall module-model calculation module-ranking module".
And step 130, recommending the article based on the connected article recommending process.
After the item recommendation module is connected, the server can call the connected item recommendation process. And calculating the recommendation score of the item according to the item recommendation process. And sorting the recommendation scores, and recommending the articles according to a sorting result.
According to the technical scheme, the determined article configuration modules are connected through determining the article configuration modules and the configuration parameters, so that an article recommendation process meeting the needs of a user is formed, the problem that in the prior art, all modules are fixed in the article recommendation process is solved, the recommendation precision of all modules during article recommendation and the influence of all modules on the final recommendation scores can be effectively known, the flexibility and the efficiency of article recommendation are improved, and the use experience of the user is improved.
Example two
Fig. 2 is a flowchart illustrating an item recommendation method according to a second embodiment of the present invention, which is further optimized based on the second embodiment.
In this embodiment, optionally, recommending the item based on the connected item recommendation process includes: obtaining a target item recommendation process selected from the at least two connected item recommendation processes; running a target article recommendation process according to an article configuration module and configuration parameters of the target article recommendation process and attribute information of the candidate article to obtain a candidate article recommendation score; and recommending the item according to the candidate item recommendation score.
As shown in fig. 2, the method specifically includes the following steps:
And step 220, connecting modules in an item recommendation process according to configuration parameters of the item configuration module, wherein the item recommendation process comprises an item configuration module or comprises the item configuration module and a basic module.
And step 230, obtaining a target item recommendation flow selected from the connected at least two item recommendation flows.
After the server obtains the article configuration module and the configuration parameters determined by the user, the article recommendation processes under the article configuration module and the configuration parameters can be stored, and a plurality of article recommendation processes can be stored in the server. The user can directly select a target item recommendation process from at least two item recommendation processes as a process for calculating the item recommendation score. Namely, the server can store the item recommendation flow in advance, and does not need to generate an item recommendation flow when the user operates every time, so that the operation time of the user is saved, and the item recommendation efficiency is improved. For example, the server stores a flow a and a flow B, and the user may establish a flow C as the target item recommendation flow, or may select the target item recommendation flow from the flow a and the flow B.
And 240, operating the target article recommendation process according to the article configuration module and the configuration parameters of the target article recommendation process and the attribute information of the candidate article to obtain the candidate article recommendation score.
The candidate item is an item to be recommended, and the attribute information of the candidate item may be information such as volume of transaction, inventory, score, click rate, and the like. Inputting the attribute information of the candidate article into a target article recommendation process, operating the target article recommendation process according to an article configuration module and configuration parameters of the target article recommendation process, and calculating the recommendation score of the candidate article.
And step 250, recommending the item according to the candidate item recommendation score.
After the recommendation scores of the candidate articles are determined, the recommendation scores are ranked, and article recommendation is performed according to the ranking result.
According to the embodiment of the invention, the determined article configuration modules are connected by determining the article configuration modules and the configuration parameters to form the article recommendation process, and a user can select from a plurality of article recommendation processes according to needs. The problem of among the prior art, each module is fixed in the article recommendation flow is solved, the recommendation precision of each module when article are recommended can be effectively known, the flexibility and the efficiency of article recommendation are improved, and the use experience of a user is improved.
EXAMPLE III
Fig. 3 is a block diagram of an article recommendation apparatus according to a third embodiment of the present invention, which is capable of executing an article recommendation method according to any embodiment of the present invention, and includes functional modules and beneficial effects corresponding to the execution method. As shown in fig. 3, the apparatus specifically includes:
a module and parameter determination module 301 for determining an item configuration module and configuration parameters of the item configuration module;
a module connection module 302, configured to connect modules in an item recommendation process according to configuration parameters of an item configuration module, where the item recommendation process includes the item configuration module, or includes the item configuration module and a base module;
and the item recommendation module 303 is configured to recommend an item based on the connected item recommendation process.
Optionally, the module and parameter determining module 301 includes:
the module obtaining unit is used for obtaining an article configuration module of the article recommendation process selected from the candidate configuration modules;
and the parameter acquisition unit is used for acquiring the configuration parameters of the article configuration module input by the user.
Optionally, before obtaining the item configuration module of the item recommendation process selected from the candidate configuration modules, the apparatus further includes:
and the module adding module is used for adding the acquired new configuration module into the candidate configuration module.
Optionally, the configuration parameters of the item configuration module include a connection relationship between different modules in the item recommendation process, and internal parameters of the item configuration module.
Optionally, the item recommendation module 303 includes:
the flow acquisition unit is used for acquiring a target item recommendation flow selected from the connected at least two item recommendation flows;
the candidate score obtaining unit is used for operating the target article recommendation process according to the article configuration module and the configuration parameters of the target article recommendation process and the attribute information of the candidate article to obtain a candidate article recommendation score;
and the score recommending unit is used for recommending the item according to the candidate item recommending score.
According to the embodiment of the invention, the determined article configuration modules are connected by determining the article configuration modules and the configuration parameters, so that an article recommendation process meeting the needs of a user is formed, the problem that each module is fixed in the article recommendation process in the prior art is solved, the recommendation precision of each module during article recommendation can be effectively known, the flexibility and the efficiency of article recommendation are improved, and the use experience of the user is improved.
Example four
Fig. 4 is a schematic structural diagram of a computer device according to a fourth embodiment of the present invention. FIG. 4 illustrates a block diagram of an exemplary computer device 400 suitable for use in implementing embodiments of the present invention. The computer device 400 shown in fig. 4 is only an example and should not bring any limitations to the functionality or scope of use of the embodiments of the present invention.
As shown in fig. 4, computer device 400 is in the form of a general purpose computing device. The components of computer device 400 may include, but are not limited to: one or more processors or processing units 401, a system memory 402, and a bus 403 that couples the various system components (including the system memory 402 and the processing unit 401).
The system memory 402 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM)404 and/or cache memory 405. The computer device 400 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 406 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 4, and commonly referred to as a "hard drive"). Although not shown in FIG. 4, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 403 by one or more data media interfaces. Memory 402 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the invention.
A program/utility 408 having a set (at least one) of program modules 407 may be stored, for example, in memory 402, such program modules 407 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which examples or some combination thereof may comprise an implementation of a network environment. Program modules 407 generally perform the functions and/or methods of the described embodiments of the invention.
The computer device 400 may also communicate with one or more external devices 409 (e.g., keyboard, pointing device, display 410, etc.), with one or more devices that enable a user to interact with the computer device 400, and/or with any devices (e.g., network card, modem, etc.) that enable the computer device 400 to communicate with one or more other computing devices. Such communication may be through input/output (I/O) interface 411. Moreover, computer device 400 may also communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network such as the Internet) via network adapter 412. As shown, network adapter 412 communicates with the other modules of computer device 400 over bus 403. It should be appreciated that although not shown in the figures, other hardware and/or software modules may be used in conjunction with computer device 400, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
The processing unit 401 executes various functional applications and data processing by executing programs stored in the system memory 402, for example, to implement an item recommendation method provided by an embodiment of the present invention, including:
determining an article configuration module and configuration parameters of the article configuration module;
connecting modules in an article recommendation process according to configuration parameters of an article configuration module, wherein the article recommendation process comprises an article configuration module or comprises the article configuration module and a basic module;
and recommending the article based on the connected article recommending process.
EXAMPLE five
The fifth embodiment of the present invention further provides a storage medium containing computer-executable instructions, where the storage medium stores a computer program, and when the computer program is executed by a processor, the method for recommending an article according to the fifth embodiment of the present invention is implemented, where the method includes:
determining an article configuration module and configuration parameters of the article configuration module;
connecting modules in an article recommendation process according to configuration parameters of an article configuration module, wherein the article recommendation process comprises an article configuration module or comprises the article configuration module and a basic module;
and recommending the article based on the connected article recommending process.
Computer storage media for embodiments of the invention may employ any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (10)
1. An item recommendation method, comprising:
determining an item configuration module and configuration parameters of the item configuration module;
connecting modules in an item recommendation process according to configuration parameters of the item configuration module, wherein the item recommendation process comprises the item configuration module or comprises the item configuration module and a basic module;
and recommending the article based on the connected article recommending process.
2. The method of claim 1, wherein determining an item configuration module and configuration parameters of the item configuration module comprises:
the item configuration module is used for acquiring the item recommendation process selected from the candidate configuration modules;
and acquiring configuration parameters of the article configuration module input by a user.
3. The method of claim 2, wherein prior to obtaining the item configuration module of the item recommendation process selected from the candidate configuration modules, the method further comprises:
and adding the acquired new configuration module into the candidate configuration module.
4. The method of claim 1, wherein the configuration parameters of the item configuration module include connection relationships between different modules in the item recommendation process and internal parameters of the item configuration module.
5. The method of claim 1, wherein performing item recommendation based on the linked item recommendation process comprises:
obtaining a target item recommendation process selected from the at least two connected item recommendation processes;
running the target article recommendation process according to the article configuration module and the configuration parameters of the target article recommendation process and the attribute information of the candidate article to obtain a candidate article recommendation score;
and recommending the item according to the candidate item recommendation score.
6. An item recommendation device, comprising:
the module and parameter determining module is used for determining an article configuration module and configuration parameters of the article configuration module;
the module connecting module is used for connecting modules in an item recommendation process according to configuration parameters of the item configuration module, wherein the item recommendation process comprises the item configuration module or comprises the item configuration module and a basic module;
and the article recommending module is used for recommending articles based on the connected article recommending process.
7. The apparatus of claim 6, wherein the module and the parameter determination module comprise:
a module obtaining unit, configured to obtain an item configuration module of the item recommendation process selected from the candidate configuration modules;
and the parameter acquisition unit is used for acquiring the configuration parameters of the article configuration module input by the user.
8. The apparatus of claim 7, wherein prior to obtaining the item configuration module of the item recommendation process selected from the candidate configuration modules, the apparatus further comprises:
and the module adding module is used for adding the acquired new configuration module into the candidate configuration module.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the item recommendation method as claimed in any one of claims 1-5 when executing the program.
10. A storage medium containing computer-executable instructions for performing the item recommendation method of any one of claims 1-5 when executed by a computer processor.
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| US20100250336A1 (en) * | 2009-03-31 | 2010-09-30 | David Lee Selinger | Multi-strategy generation of product recommendations |
| CN106600302A (en) * | 2015-10-19 | 2017-04-26 | 玺阅信息科技（上海）有限公司 | Hadoop-based commodity recommendation system |
| CN107679882A (en) * | 2016-08-01 | 2018-02-09 | 长沙有干货网络技术有限公司 | A kind of Hadoop Technologies of Recommendation System in E-Commerce |
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2020
- 2020-05-18 CN CN202010418745.5A patent/CN111612580A/en active Pending
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| Publication number | Priority date | Publication date | Assignee | Title |
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| US20100250336A1 (en) * | 2009-03-31 | 2010-09-30 | David Lee Selinger | Multi-strategy generation of product recommendations |
| CN106600302A (en) * | 2015-10-19 | 2017-04-26 | 玺阅信息科技（上海）有限公司 | Hadoop-based commodity recommendation system |
| CN107679882A (en) * | 2016-08-01 | 2018-02-09 | 长沙有干货网络技术有限公司 | A kind of Hadoop Technologies of Recommendation System in E-Commerce |
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