CN110597962A

CN110597962A - Search result display method, device, medium and electronic equipment

Info

Publication number: CN110597962A
Application number: CN201910901027.0A
Authority: CN
Inventors: 李德苑; 郑纪; 罗雅愉
Original assignee: Tencent Technology Shenzhen Co Ltd
Current assignee: Tencent Technology Shenzhen Co Ltd
Priority date: 2019-09-23
Filing date: 2019-09-23
Publication date: 2019-12-20
Anticipated expiration: 2039-09-23
Also published as: CN110597962B

Abstract

The disclosure provides a search result display method, a search result display device, a search result display medium and electronic equipment based on artificial intelligence. The method in the embodiment of the disclosure comprises the following steps: receiving a search request, and determining an index keyword according to the search request; searching a target brand main body in a brand database according to the index key words, and acquiring brand main body attribute information of the target brand main body; determining an application program main body and an information dissemination main body which are associated with the target brand main body, and acquiring program main body link information corresponding to the application program main body and dissemination main body link information corresponding to the information dissemination main body; and generating a search result display page according to the brand main body attribute information, the program main body link information and the propagation main body link information. The method can improve the searching accuracy and searching efficiency, and meanwhile can provide richer and more visual rich media type brand information display effect for the user.

Description

Search result display method, device, medium and electronic equipment

Technical Field

The present disclosure relates to the field of artificial intelligence technologies, and in particular, to a search result display method based on artificial intelligence, a search result display apparatus based on artificial intelligence, a computer-readable medium, and an electronic device.

Background

With the development of computer and network technologies, brand promotion over the internet and provision of products and services to users over the internet have become increasingly routine choices for brand owners. On the basis, a plurality of network platforms capable of providing brand publicity channels and product and service sale channels for brand main bodies are derived. For example, a user can find out public numbers or applets of various brands through a functional interface provided by the WeChat platform, so as to obtain products or services provided by brand subjects.

However, due to the complexity of brand network resources and the diversity of brand service forms, when a user searches for related brands or products, services and other contents through a network platform, a search result is often doped with a lot of noise information, and the user needs to carefully identify and screen layer by layer to find an accurate brand main body. Moreover, even if the exact brand identity is found, jumps through multiple layers of web pages or application pages are required to reach a specific product purchase page or service page. Therefore, how to improve the searching accuracy and searching efficiency of the brand is a problem to be solved urgently at present.

It is to be noted that the information disclosed in the above background section is only for enhancement of understanding of the background of the present application and therefore may include information that does not constitute prior art known to a person of ordinary skill in the art.

Disclosure of Invention

The present disclosure is directed to a search result display method based on artificial intelligence, a search result display apparatus based on artificial intelligence, a computer readable medium and an electronic device, so as to overcome technical problems of poor brand search accuracy, low search efficiency and the like caused by limitations of related technologies at least to a certain extent.

Additional features and advantages of the disclosure will be set forth in the detailed description which follows, or in part will be obvious from the description, or may be learned by practice of the disclosure.

According to an aspect of the embodiments of the present disclosure, there is provided a search result presentation method based on artificial intelligence, the method including: receiving a search request, and determining an index keyword according to the search request; searching a target brand main body in a brand database according to the index key words, and acquiring brand main body attribute information of the target brand main body; determining an application program main body and an information dissemination main body which are associated with the target brand main body, and acquiring program main body link information corresponding to the application program main body and dissemination main body link information corresponding to the information dissemination main body; and generating a search result display page according to the brand main body attribute information, the program main body link information and the propagation main body link information.

According to an aspect of the embodiments of the present disclosure, there is provided an artificial intelligence-based search result presentation apparatus, including: the keyword determining module is configured to receive a search request and determine an index keyword according to the search request; the attribute information acquisition module is configured to retrieve a target brand main body from a brand database according to the index key words and acquire brand main body attribute information of the target brand main body; a link information acquisition module configured to determine an application program main body and an information dissemination main body associated with the target brand main body, and acquire program main body link information corresponding to the application program main body and dissemination main body link information corresponding to the information dissemination main body; and the display page generating module is configured to generate a search result display page according to the brand main body attribute information, the program main body link information and the propagation main body link information.

In some embodiments of the present disclosure, based on the above technical solutions, the keyword determination module includes: the search information acquisition module is configured to acquire search information carried in the search request; a semantic recognition module configured to perform semantic recognition on the search information to obtain basic keywords in the search information; a keyword expansion module configured to obtain expanded keywords related to the basic keywords, and determine the basic keywords and the expanded keywords as index keywords.

In some embodiments of the present disclosure, based on the above technical solutions, the attribute information obtaining module includes: the candidate brand retrieval module is configured to retrieve a plurality of candidate brand main bodies from a brand database according to the index key words; a recommendation information acquisition module configured to determine an information dissemination subject associated with the candidate brand subject and acquire brand recommendation information corresponding to the information dissemination subject; a target brand determination module configured to select one or more candidate brand principals as target brand principals according to the brand recommendation information.

In some embodiments of the present disclosure, based on the above technical solutions, the attribute information obtaining module includes: the candidate brand retrieval module is configured to retrieve a plurality of candidate brand main bodies from a brand database according to the index key words; an information dissemination body determination module configured to determine an information dissemination body associated with the candidate brand body and acquire an exposure rate, an associated user number, and category information of the information dissemination body; a recommendation coefficient determination module configured to determine a brand recommendation coefficient of the information dissemination subject according to the exposure rate, the number of associated users, and category information; and the target brand determining module is configured to rank the plurality of candidate brand subjects according to the brand recommendation coefficient and determine a target brand subject according to the ranked candidate brand subjects.

In some embodiments of the present disclosure, based on the above technical solution, the index key includes a brand principal index key and an application index key; the attribute information acquisition module includes: a brand recall module configured to retrieve a brand recall keyword of a brand principal in a brand database using the brand principal index keyword; a candidate brand determination module configured to determine a brand principal for which the brand recall keyword matches the brand principal index keyword as a candidate brand principal and determine a candidate application principal associated with the candidate brand principal; a program recall module configured to retrieve an application recall keyword of the candidate application subject in a brand database using the application index keyword; a brand matching module configured to determine a candidate application subject for which the application recall keyword matches the application index keyword as a target application subject and determine a candidate brand subject associated with the target application subject as a target brand subject.

In some embodiments of the present disclosure, based on the above technical solutions, the apparatus further includes: a target service item determining module configured to determine a target service item provided by the target application main body according to the application recall keyword and acquire service item link information corresponding to the target service item; the display page generation module is configured to generate a search result display page according to the brand main body attribute information, the program main body link information and the propagation main body link information, and in combination with the service item link information.

In some embodiments of the present disclosure, based on the above technical solutions, the apparatus further includes: a recommended service item determination module configured to determine a recommended service item provided by the application main body and acquire service item connection information corresponding to the recommended service item; the display page generation module is configured to generate a search result display page according to the brand main body attribute information, the program main body link information and the propagation main body link information, and in combination with the service item link information.

According to an aspect of the embodiments of the present disclosure, there is provided a computer readable medium, on which a computer program is stored, which when executed by a processor implements the artificial intelligence based search result presentation method as in the above technical solutions.

According to an aspect of an embodiment of the present disclosure, there is provided an electronic apparatus including: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to execute the artificial intelligence based search result presentation method as in the above technical solution via executing the executable instructions.

In the technical scheme provided by the embodiment of the disclosure, the association relationship is established for the brand main body and the plurality of brand association objects, so that the related information can be integrated and displayed in the brand information search, the search accuracy and the search efficiency are improved, meanwhile, a richer and more visual rich-media brand information display effect can be provided for a user, and the user can more quickly and accurately acquire products and services provided by the brand main body. In addition, the multiple kinds of associated information are displayed together, so that the interference of noise information on a target brand main body can be avoided, and a user can visually distinguish a regular brand from an emulational brand from multiple dimensions such as brand introduction, applets and public numbers.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure. It is to be understood that the drawings in the following description are merely exemplary of the disclosure, and that other drawings may be derived from those drawings by one of ordinary skill in the art without the exercise of inventive faculty. In the drawings:

fig. 1 shows an exemplary system architecture diagram to which the disclosed solution is applied.

FIG. 2 schematically illustrates a flow chart of steps of an artificial intelligence based search result presentation method in some embodiments of the present disclosure.

FIG. 3 schematically shows a flow chart of steps for determining index keys in some embodiments of the present disclosure.

FIG. 4 schematically shows a flowchart of steps for retrieving target brand principals based on brand recommendation information in some embodiments of the present disclosure.

FIG. 5 schematically shows a flowchart of steps for retrieving target brand principals based on brand recommendation coefficients in some embodiments of the present disclosure.

FIG. 6 schematically shows a flow chart of steps for retrieving brand principals based on a variety of keywords in some embodiments of the present disclosure.

FIG. 7 schematically illustrates a frame diagram of a social platform server building a brand retrieval system from merchant uploaded material.

FIG. 8 schematically illustrates an interactive interface diagram showing search results to a user on a mobile terminal.

FIG. 9 schematically illustrates a data sharing system for maintaining data related to brand principals in some embodiments of the present disclosure.

Fig. 10 schematically illustrates the composition of a blockchain in some embodiments of the present disclosure.

Fig. 11 schematically illustrates a process of generating a tile from a blockchain in some embodiments of the present disclosure.

FIG. 12 schematically illustrates a block diagram of an artificial intelligence based search results presentation apparatus in some embodiments of the present disclosure.

FIG. 13 illustrates a schematic structural diagram of a computer system suitable for use in implementing the electronic device of an embodiment of the present disclosure.

Detailed Description

Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art.

Furthermore, the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the disclosure. One skilled in the relevant art will recognize, however, that the subject matter of the present disclosure can be practiced without one or more of the specific details, or with other methods, components, devices, steps, and so forth. In other instances, well-known methods, devices, implementations, or operations have not been shown or described in detail to avoid obscuring aspects of the disclosure.

The block diagrams shown in the figures are functional entities only and do not necessarily correspond to physically separate entities. I.e. these functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor means and/or microcontroller means.

The flow charts shown in the drawings are merely illustrative and do not necessarily include all of the contents and operations/steps, nor do they necessarily have to be performed in the order described. For example, some operations/steps may be decomposed, and some operations/steps may be combined or partially combined, so that the actual execution sequence may be changed according to the actual situation.

In the related art of the present disclosure, a brand owner may implement activities such as brand publicity or product sales using a self-developed network platform or by means of a third-party network platform. For example, a certain brand principal may build an official website or a network mall by itself, or may set up a social account, an application program, an online store, and the like on a third-party network platform such as WeChat, microblog, Taobao, Jingdong mall, and the like. Using the WeChat platform as an example, a brand owner may run and maintain a community number or applet for advertising or providing products and services. However, the search of the public number or the applet is generally based on the name and description content of the relevant subject, so the search result is quite complicated, and various kinds of noise information exist. Moreover, the mere names and descriptions often do not accurately describe the core functions of the public account or the applet itself. Therefore, when the user searches for the application service, the public numbers or the applets with higher relevance to the search words cannot obtain the exposure, and therefore the user cannot quickly and accurately find the required products or services. In addition, in the aspect of display morphology, the search results of the public numbers or the applets cannot provide simple and direct services for the users, and the users need to perform multi-layer jumping inside the public numbers or the applets to obtain specific products or services.

Based on the problems of the above schemes, the present disclosure provides an artificial intelligence based search result presentation method, an artificial intelligence based search result presentation apparatus, a computer readable medium, and an electronic device that can provide an accurate recall and a direct service function.

As shown in fig. 1, system architecture 100 may include a client 110, a network 120, and a server 130. The client 110 may include various terminal devices such as a smart phone, a tablet computer, a notebook computer, and a desktop computer. The server 130 may include various server devices such as a web server, an application server, a database server, and the like. Network 120 may be a communication medium of various connection types capable of providing communication links between clients 110 and servers 130, such as wired communication links, wireless communication links, and so forth.

The system architecture in the embodiments of the present disclosure may have any number of clients, networks, and servers, as desired for implementation. For example, the server 130 may be a server group consisting of a plurality of server devices. In addition, the search result display method based on artificial intelligence in the embodiment of the present disclosure may be applied to the client 110, and may also be applied to the server 130, which is not particularly limited in the present disclosure.

For example, when the artificial intelligence based search result presentation method provided by the embodiment of the present disclosure is applied to the server 130, a user may fill in search information related to content such as brands, products, or services in a search interface of the client 110, and the client 110 generates a corresponding search request according to the search information and sends the search request to the server 130 through the network 120. The server 130, in response to the received search request, may perform semantic analysis on information carried in the search request to obtain corresponding index keywords, then determine a target brand main body, an application program main body and an information dissemination main body associated with the target brand main body by using the index keywords, and finally generate a search result display page according to the brand main body attribute information, the program main body link information and the dissemination main body link information. The server 130 returns the page data of the search result display page to the client 110 through the network 120, and the client 110 renders the page data and displays the rendered page data on a display interface.

In some optional embodiments, the server 130 may further be configured with an Artificial Intelligence (AI) processing function module, and implement method steps of obtaining an index keyword, determining a target brand main body, and the like by using technologies such as a voice technology, natural language processing, machine learning, and the like.

Artificial intelligence is a theory, method, technique and application system that uses a digital computer or a machine controlled by a digital computer to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use the knowledge to obtain the best results. In other words, artificial intelligence is a comprehensive technique of computer science that attempts to understand the essence of intelligence and produce a new intelligent machine that can react in a manner similar to human intelligence. Artificial intelligence is the research of the design principle and the realization method of various intelligent machines, so that the machines have the functions of perception, reasoning and decision making.

The artificial intelligence technology is a comprehensive subject and relates to the field of extensive technology, namely the technology of a hardware level and the technology of a software level. The artificial intelligence infrastructure generally includes technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing technologies, operation/interaction systems, mechatronics, and the like. The artificial intelligence software technology mainly comprises a computer vision technology, a voice processing technology, a natural language processing technology, machine learning/deep learning and the like.

Key technologies for Speech Technology (ST) are automatic Speech recognition Technology (ASR) and Speech synthesis Technology (TTS) as well as voiceprint recognition Technology. The computer can listen, see, speak and feel, and the development direction of the future human-computer interaction is provided, wherein the voice becomes one of the best viewed human-computer interaction modes in the future.

Natural Language Processing (NLP) is an important direction in the fields of computer science and artificial intelligence. It studies various theories and methods that enable efficient communication between humans and computers using natural language. Natural language processing is a science integrating linguistics, computer science and mathematics. Therefore, the research in this field will involve natural language, i.e. the language that people use everyday, so it is closely related to the research of linguistics. Natural language processing techniques typically include text processing, semantic understanding, machine translation, robotic question and answer, knowledge mapping, and the like.

Machine Learning (ML) is a multi-domain cross discipline, and relates to a plurality of disciplines such as probability theory, statistics, approximation theory, convex analysis, algorithm complexity theory and the like. The special research on how a computer simulates or realizes the learning behavior of human beings so as to acquire new knowledge or skills and reorganize the existing knowledge structure to continuously improve the performance of the computer. Machine learning is the core of artificial intelligence, is the fundamental approach for computers to have intelligence, and is applied to all fields of artificial intelligence. Machine learning and deep learning generally include techniques such as artificial neural networks, belief networks, reinforcement learning, transfer learning, inductive learning, and formal education learning.

The artificial intelligence based search result presentation method, the artificial intelligence based search result presentation apparatus, the computer readable medium, and the electronic device provided by the present disclosure are described in detail below with reference to specific embodiments.

FIG. 2 schematically illustrates a flow chart of steps of an artificial intelligence based search result presentation method in some embodiments of the present disclosure. As shown in fig. 2, the method may mainly include the following steps:

step S210, receiving a search request, and determining index keywords according to the search request.

According to the search requirement of the user, the search request can be generated through a client program or a network page. After receiving the search request, the client device or the server device may determine a corresponding index key. The index key may be a key related to a brand name, a commodity name, service information, and the like. In addition, the index keyword may be a keyword directly input by a user when generating a search request or a keyword obtained by analyzing and extracting information input by the user, or may be a keyword automatically generated by the user by clicking or selecting a tag or an option provided by a search interface under the search interface. For example, the index key may be "express", "china mobile", "mcdonald' and the like.

And S220, retrieving the target brand main body from the brand database according to the index key words, and acquiring the brand main body attribute information of the target brand main body.

In order to improve the accuracy of brand information search, the embodiments of the present disclosure may pre-configure and maintain a brand database for storing introduction information of various brand principals and network acquisition interfaces of various products or services related to the brand principals. Each brand principal may configure and manage its own related material and associated information, which may include, for example, product listings, product purchase links, service listings, service information, WeChat public numbers, WeChat applets, and so forth. The brand database may uniformly maintain the search elements of the brand subjects, and the search elements of the brand subjects may be compared according to the index key words obtained in step S210, and the successfully compared brand subjects are regarded as target brand subjects. And aiming at the target brand main body obtained by searching, the step also obtains the attribute information of the brand main body. The brand principal attribute information may primarily include one or more of a brand principal name, a brand principal identity, a brand principal introduction, and a brand authentication identity. The brand subject name may be a common name or nickname for the brand subject, such as "china mobile", "10086", "china mobile 10086", and so forth. The brand principal mark can be LOGO information such as a trademark of a brand, LOGO and the like. The brand principal introduction may be descriptive text relating to the content of the brand principal's services, products, etc. The brand authentication mark may be authentication mark information of the property or attribute of the brand main body, for example, the public number accessed to the brand search may be analyzed by integrating information such as exposure rate, fan number, category and the like, and an authentication mark such as "official" is provided for the brand main body meeting specific requirements.

Step S230, determining an application program main body and an information dissemination main body which are associated with the target brand main body, and acquiring program main body link information corresponding to the application program main body and dissemination main body link information corresponding to the information dissemination main body.

With respect to the target brand principal determined in step S220, this step may determine one or more brand associated objects associated with the target brand principal according to the association relationship between each brand principal and each associated object. The brand-associated object may include at least an information dissemination body for disseminating brand information and an application body for providing a brand service, and may also include a set of products or a set of service items provided by the brand body. The brand owner may manage and maintain a product set for presentation in search results, for example, a certain mobile phone brand may make up the latest mobile phone products on the market into a product set. The associated object exposure information corresponding to the product set may include names, models, images, prices, purchase links, and the like of the respective products in the product set. The information dissemination body may be a network information dissemination interface or channel for disseminating brand information. For example, the information dissemination subject may be a public broadcasting subject such as an official website and a microblog account, or a group broadcasting subject such as a wechat public number and a pay-for-life number. The link information of the propagation body can be directly jumped to an information propagation page provided by the information propagation body, for example, a public number page corresponding to the target brand body. The application may be a program client or a wechat applet or the like for providing branding services. The corresponding application main body can be directly opened by utilizing the application link information, for example, a program client or an applet provided by the target brand main body can be opened.

And S240, generating a search result display page according to the brand main body attribute information, the program main body link information and the propagation main body link information.

Based on the target brand principal determined in step S220, a search result presentation page may be generated that is composed of one or more search terms, each corresponding to a target brand principal. Moreover, the presentation content in each search entry may include at least three components, namely, brand principal attribute information, program principal link information, and disseminate principal link information related to the target brand principal.

In the search result display method based on artificial intelligence provided by the embodiment of the disclosure, by establishing an association relationship for a plurality of brand association objects such as a brand main body, an application main body and an information dissemination main body, relevant information can be integrated and displayed in the brand information search, and the search accuracy and the search efficiency are improved, and meanwhile, a richer and more intuitive rich media type brand information display effect can be provided for a user, so that the user can more quickly and accurately acquire products and services provided by the brand main body. In addition, the multiple kinds of associated information are displayed together, so that the interference of noise information on a target brand main body can be avoided, and a user can visually distinguish a regular brand from an emulational brand from multiple dimensions such as brand introduction, applets and public numbers.

FIG. 3 schematically shows a flow chart of steps for determining index keys in some embodiments of the present disclosure. As shown in fig. 3, on the basis of the above embodiment, the determining the index key according to the search request in step S210 may include the following steps:

and S310, acquiring search information carried in the search request.

The user can input search information on the client device in a voice, text or gesture interaction mode and the like, and then a search request generated according to the search information is sent to the server side by the client side, or the server side actively obtains the search request from the client side. The server analyzes the search request to obtain the search information carried in the search request, wherein the search information can be expressed as a single character, a word formed by one or more characters or a sentence formed by a plurality of words. For example, a user inputs information "i want to send an express delivery" at a client by using a voice function, and a search request carrying the information is sent to a server and is analyzed and acquired by the server.

And S320, performing semantic recognition on the search information to obtain basic keywords in the search information.

Useless information in the search information can be stripped through semantic recognition of the search information, and therefore basic keywords related to the user intention can be obtained. The semantic recognition in this step may specifically adopt a method of named entity recognition, for example, a pre-written regular expression may be used to perform regular matching detection on the search information, or a word search tree (Trie) may be used to perform word matching detection on the search information, or a pre-trained machine learning model may be used to perform named entity recognition on the search information. The search information is subjected to semantic recognition to obtain one or more basic keywords, and the number of the basic keywords depends on the information content and specific semantics of the search information.

And S330, acquiring the expanded keywords related to the basic keywords, and determining the basic keywords and the expanded keywords as the index keywords.

According to the method and the device for searching the brand database, the corresponding keyword library can be configured in the brand database, when the basic keywords are obtained from the search information, the basic keywords can be searched in the keyword library, and the expansion keywords with the same or similar semantics as the basic keywords can be obtained. For example, if the basic keyword is "express", the obtained expanded keywords may include "package", "mail", "post", "leg running", and the like. In some alternative embodiments, this step may also extend the basic keywords using a pre-trained machine learning model. The basic keywords and the expanded keywords are determined as the index keywords together, so that the recall rate of the brand main body can be greatly improved, and the probability of hitting the search requirements of the user is increased.

In addition to the recall rate of the brand subjects, the retrieval accuracy rate of the brand subjects is an important factor influencing the search results, and in order to improve the retrieval accuracy rate of the brand subjects, the disclosure can provide a target brand subject retrieval method based on factors such as brand recommendation information or brand recommendation coefficients.

FIG. 4 schematically shows a flowchart of steps for retrieving target brand principals based on brand recommendation information in some embodiments of the present disclosure. As shown in fig. 4, on the basis of the above embodiments, the step S220 of retrieving the target brand main body from the brand database according to the index key may include the following steps:

and S410, searching a plurality of candidate brand main bodies in the brand database according to the index key words.

The index key may be a key related to a brand name, or a key related to contents such as a product name provided by a brand, a service item, or a service field to which the brand belongs. Generally, a plurality of candidate brand subjects can be searched in the brand database by using the index key words as search elements, and most of the candidate brand subjects are brand subjects with similar names, the same service field or other related characteristics.

And S420, determining an information dissemination main body associated with the candidate brand main body, and acquiring brand recommendation information corresponding to the information dissemination main body.

For each candidate brand principal retrieved in step S410, this step may determine an information dissemination principal associated with each candidate brand principal, for example, may determine a public number associated with each candidate brand principal. For each information dissemination subject, corresponding brand recommendation information can be configured in the brand database in advance, for example, all public numbers can be divided into official public numbers and unofficial public numbers according to account subject information of the public numbers. Wherein official public numbers have a higher degree of recommendation, while non-official public numbers have a relatively lower degree of recommendation.

And S430, selecting one or more candidate brand subjects as target brand subjects according to the brand recommendation information.

According to the brand recommendation information corresponding to the information dissemination subject, the plurality of candidate brand subjects obtained by searching can be screened, and one or more candidate brand subjects with higher recommendation degrees are selected as the target brand subjects.

When information transmission subjects such as public numbers are operated online, authentication data generally need to be submitted to a public number operation platform, and after the public number operation platform verifies the relevant authentication data, authentication can be performed on operation subjects corresponding to the public numbers. The candidate brand subjects authenticated by the official may be preferentially presented to the user as target brand subjects using the authentication result of the public number as the brand recommendation information.

FIG. 5 schematically shows a flowchart of steps for retrieving target brand principals based on brand recommendation coefficients in some embodiments of the present disclosure. As shown in fig. 5, on the basis of the above embodiments, the step S220 of retrieving the target brand main body from the brand database according to the index key may include the following steps:

and S510, searching a plurality of candidate brand main bodies in the brand database according to the index key words.

The way of retrieving the candidate brand main body is similar to the previous embodiment, and is not described herein again.

And S520, determining an information dissemination body associated with the candidate brand body, and acquiring the exposure rate, the number of associated users and the category information of the information dissemination body.

Still taking the public number as an example, after the public numbers associated with each candidate brand principal are determined separately, this step may obtain the exposure rate, the number of associated users, and category information of the respective public numbers. The exposure rate refers to the number of times of displaying the public account in unit time, the number of related users may be, for example, the number of interested users of the public account, and the category information may include different public account types such as subscription numbers, service numbers, or enterprise WeChat.

And S530, determining the brand recommendation coefficient of the information dissemination main body according to the exposure rate, the number of the associated users and the category information.

The exposure rate, the number of associated users and the category information are analyzed to determine a brand recommendation coefficient of the information dissemination subject, for example, the three information can be quantitatively characterized and then weighted according to different weights to obtain the brand recommendation coefficient of the information dissemination subject.

And S540, sequencing the plurality of candidate brand main bodies according to the brand recommendation coefficients, and determining a target brand main body according to the sequenced candidate brand main bodies.

The plurality of candidate brand subjects may be ranked according to the magnitude of the brand recommendation coefficient, and then the target brand subject may be determined according to the ranking result, for example, several candidate brand subjects ranked in the top may be directly determined as the target brand subject, or several candidate brand subjects whose brand recommendation coefficient is greater than a certain threshold may be determined as the target brand subject.

In some embodiments of the present disclosure, the index key for brand principal retrieval may further include a brand principal index key and an application index key. When a plurality of index keywords are determined according to the search request, the embodiment of the present disclosure may perform type recognition on the index keywords, determine a part of the index keywords as brand main body index keywords, and determine other index keywords except the brand main body index keywords as application index keywords. FIG. 6 schematically shows a flow chart of steps for retrieving brand principals based on a variety of keywords in some embodiments of the present disclosure. As shown in fig. 6, on the basis of the above embodiments, the step S220 of retrieving the target brand main body from the brand database according to the index key may include the following steps:

step S610, utilizing the brand principal index key words to search the brand recall key words of the brand principal in the brand database.

Each brand principal may be configured with a corresponding brand recall key in the brand principal database for retrieval recall thereof. The brand recall keyword may be a keyword related to the name of the brand principal, the product, the service, etc. The method comprises the following steps of firstly, retrieving and comparing brand recalling keywords corresponding to each brand main body in a brand database by using the brand main body index keywords so as to judge whether the brand main body index keywords can be successfully matched with the brand recalling keywords.

Step S620, the brand main body with the matched brand recall keyword and the brand main body index keyword is determined as a candidate brand main body, and a candidate application program main body associated with the candidate brand main body is determined.

When a certain brand recall keyword can be successfully matched with the brand principal index keyword, the brand principal corresponding to the brand recall keyword can be determined as a candidate brand principal. Meanwhile, the step may determine a candidate application program principal associated with the candidate brand principal according to a preconfigured association relationship.

Step S630, the application recall keywords of the candidate application main bodies are searched in the brand database by utilizing the application index keywords.

To improve recall accuracy of brand principals, application recall keywords may be configured in the brand database for application principals associated with the brand principals. In the step, the application program index key words and the application program recall key words corresponding to the candidate application program main bodies are searched and compared to judge whether the application program index key words can be successfully matched with the application program recall key words or not. In some alternative embodiments, the brand recall keywords may be crossed over the application recall keywords, e.g., some keywords may be both brand recall keywords and application recall keywords.

And step 640, determining the candidate application program main body with the application program recall keyword matched with the application program index keyword as a target application program main body, and determining the candidate brand main body associated with the target application program main body as a target brand main body.

If an application recall key matches an application index key successfully, then the candidate application body corresponding to the application recall key may be identified as the target application body. Accordingly, a candidate brand principal associated with the target application principal may be determined as the target brand principal.

For example, when two index keywords are determined from a search request, one of the keywords may be identified as a brand index keyword associated with a brand principal name of a brand principal, while the other keyword is identified as an application index keyword associated with an application principal. For example, if the user inputs two keywords "hua ye" and "mobile phone" at the same time, the search keyword "huaye" as the brand index keyword may determine that the brand subject is "huaye" through search and comparison, and the search keyword "mobile phone" as the application index keyword may determine that the application subject associated with the brand subject "huaye" is "huaye +" applet through search and comparison. The two search keywords simultaneously hit the brand main body and the application program main body which have the association relationship, so that the corresponding brand main body can be recalled, and brand information search results related to the brand main body display information and the association object display information are generated. Conversely, if two search keywords cannot hit a brand principal and an application principal having an association at the same time, it may be considered that there is no corresponding brand principal in the brand database, and thus, an erroneous or inaccurate search result is prevented from being provided to the user.

On the basis of utilizing the brand index key words and the application program index key words to retrieve the target brand main bodies, the embodiment of the disclosure can also determine the target service items provided by the target application program main bodies according to the successfully matched application program recall key words, and meanwhile, obtain the service item connection information corresponding to the target service items. For example, when the target brand main body is "china mobile", the target application program main body associated with the target brand main body is "china mobile 10086 +" applet, and based on the application program recalling the keyword "telephone charge", it can be determined that the corresponding target service item includes service items related to the keyword "telephone charge", such as "telephone charge query", "telephone charge supplement", and the like, provided by the applet. For the determined target service item, when the search result presentation page is generated, the service item link information corresponding to the target service item can be presented while the brand subject attribute information, the program subject link information, and the propagation subject link information are presented. And jumping to a corresponding applet service page by using the service item link information, so that the user can directly obtain the service item which the user wants to use.

In addition, when only the brand index key is included in the index key, the embodiment of the disclosure may acquire the recommended service item provided by the application main body after determining the application main body associated with the target brand main body, and acquire the service item link information corresponding to the recommended service item. For example, when the target brand main body is "china mobile", the target application program main body associated therewith is "china mobile 10086 +" applet, and the recommended service items provided by the applet may include "traffic query", "recharge payment", and other service items preferentially recommended by the applet. For the determined recommended service item, when the search result presentation page is generated, the service item link information corresponding to the recommended service item may be presented while the brand subject attribute information, the program subject link information, and the propagation subject link information are presented. The method and the device for recommending the service items can intelligently determine the recommended service items according to the using habits of the user or information such as historical using records of the application program main body, and the like, so that the convenience of using the relevant service items by the user is improved.

The application of the search result display method based on artificial intelligence in the embodiment of the present disclosure to both sides of a social platform server and a mobile terminal is described below.

FIG. 7 schematically illustrates a frame diagram of a social platform server building a brand retrieval system from merchant uploaded material. As shown in fig. 7, the merchant 710 may upload materials related to its brand, which may specifically include brand introduction information and information of a public number, an applet, or other associated object associated with the brand body, to the social platform server 720, so as to achieve an effect of enriching the brand display content. The social platform server 720 may build a brand database 730 comprising at least a keyword library 731 and an associated material library 732 according to the related materials and associated information uploaded by the merchant 710. The keyword library 731 stores recall keywords corresponding to brand subjects, and the related material library 732 stores information on public numbers, applets, or other related objects associated with the brand subjects. Brand retrieval system 740 may be established based on brand database 730 for performing retrieval matching on a user's search requirements, thereby providing the user with search results including attribute information, association information, and the like of the brand principal.

FIG. 8 schematically illustrates an interactive interface diagram showing search results to a user on a mobile terminal. As shown in fig. 8, when a user needs to inquire brand information, view contents published by a public number, or use goods or services provided by an applet, the user may first log in to a social platform on a mobile terminal. A plurality of functional entries such as "friend circle", "scan", "search and search" are provided in the interactive interface 810 of the social platform.

The user may enter the search page 820 by clicking "search for a search" or by sending a voice command, a search box 821 is provided within the search page 820, and the user may input search information in text form or voice form using the search box 821. A search request can be generated on the mobile terminal according to the search information, and the search request is sent to the social platform server through network communication.

The social platform server analyzes the received search request to determine index keywords, then searches and matches in a brand database by using a brand retrieval system, and a search result is returned to the mobile terminal.

The mobile terminal may generate a search result display page 830 after rendering the relevant data. Multiple search entries corresponding to different brand principals may be presented simultaneously in search results presentation page 830. Each search entry includes two display portions, a brand main display area 831 and an associated object display area 832.

Brand entity display area 831 is used to display brand entity attribute information for the brand entity, which may include, for example, a brand entity name, a brand entity identifier, a brand entity introduction, and a brand authentication identifier, among others.

The associated object presentation area 832 may further include a service item presentation area 8321, an application body presentation area 8322, and an information dissemination body presentation area 8323. The service item display area 8321 is used for displaying a product list or a service list associated with the target brand main body, and mainly includes service items provided by the application program main body; an application body presentation area 8322 may be used to present applications associated with the brand body, e.g., may present a program jump entry corresponding to a program client jump link or an applet jump link; the information dissemination subject presentation area 8323 may be used to present a public broadcast subject or a group broadcast subject associated with the brand subject, for example, a page jump entry corresponding to a public number jump link or an official website jump link may be presented.

When a user clicks on brand principal presentation area 831 within a search entry, a detail presentation page for the corresponding brand principal may be entered. When the user clicks one of the display objects in the associated object display area 832, the user may jump to a display page of other associated content such as a corresponding public number, an applet, or a service item provided by the applet.

In some embodiments of the present disclosure, various data such as brand principal information, brand association object information, etc. in the brand database may be shared for storage using blockchain techniques. FIG. 9 schematically illustrates a data sharing system for maintaining data related to brand principals in some embodiments of the present disclosure. As shown in fig. 9, the data sharing system 900 refers to a system for performing data sharing between nodes, the data sharing system may include a plurality of nodes 910, and the plurality of nodes 910 may refer to respective clients in the data sharing system. Each node 910 may receive input information while operating normally and maintain shared data within the data sharing system based on the received input information. In order to ensure information intercommunication in the data sharing system, information connection can exist between each node in the data sharing system, and information transmission can be carried out between the nodes through the information connection. For example, when an arbitrary node in the data sharing system receives input information, other nodes in the data sharing system acquire the input information according to a consensus algorithm, and store the input information as data in shared data, so that the data stored on all the nodes in the data sharing system are consistent.

Each node in the data sharing system has a node identifier corresponding thereto, and each node in the data sharing system may store a node identifier of another node in the data sharing system, so that the generated block is broadcast to the other node in the data sharing system according to the node identifier of the other node in the following. Each node may maintain a node identifier list as shown in the following table, and store the node name and the node identifier in the node identifier list correspondingly. The node identifier may be an IP (Internet Protocol) address and any other information that can be used to identify the node, and table 1 only illustrates the IP address as an example.

Node name	Node identification
		Node 1	117.114.151.174
Node 2	117.116.189.145
		…	…
Node N	119.123.789.258

Each node in the data sharing system stores one identical blockchain. The block chain is composed of a plurality of blocks, and fig. 10 schematically shows a composition structure of the block chain in some embodiments of the present disclosure. As shown in fig. 10, the block chain is composed of a plurality of blocks, the starting block includes a block header and a block body, the block header stores an input information feature value, a version number, a timestamp, and a difficulty value, and the block body stores input information; the next block of the starting block takes the starting block as a parent block, the next block also comprises a block head and a block main body, the block head stores the input information characteristic value of the current block, the block head characteristic value of the parent block, the version number, the timestamp and the difficulty value, and the like, so that the block data stored in each block in the block chain is associated with the block data stored in the parent block, and the safety of the input information in the block is ensured.

Fig. 11 schematically illustrates a process of generating a tile from a blockchain in some embodiments of the present disclosure. As shown in fig. 11, when receiving input information, a node where a block chain is located verifies the input information, and after completing the verification, stores the input information in a memory pool, and updates a hash tree used for recording the input information; and then, updating the updating time stamp to the time when the input information is received, trying different random numbers, and calculating the characteristic value for multiple times, so that the calculated characteristic value can meet the following formula:

SHA256(SHA256(version+prev_hash+merkle_root+ntime+nbits+x))<TARGET

wherein, SHA256 is a characteristic value algorithm used for calculating a characteristic value; version is version information of the relevant block protocol in the block chain; prev _ hash is a block head characteristic value of a parent block of the current block; merkle _ root is a characteristic value of the input information; ntime is the update time of the update timestamp; nbits is the current difficulty, is a fixed value within a period of time, and is determined again after exceeding a fixed time period; x is a random number; TARGET is a feature threshold, which can be determined from nbits.

Therefore, when the random number meeting the formula is obtained through calculation, the information can be correspondingly stored, and the block head and the block main body are generated to obtain the current block. And then, the node where the block chain is located respectively sends the newly generated blocks to other nodes in the data sharing system where the newly generated blocks are located according to the node identifications of the other nodes in the data sharing system, the newly generated blocks are verified by the other nodes, and the newly generated blocks are added to the block chain stored in the newly generated blocks after the verification is completed.

It should be noted that although the various steps of the methods of the present disclosure are depicted in the drawings in a particular order, this does not require or imply that these steps must be performed in this particular order, or that all of the depicted steps must be performed, to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step execution, and/or one step broken down into multiple step executions, etc.

The following describes embodiments of an apparatus of the present disclosure, which may be used to implement the artificial intelligence based search result presentation method in the above embodiments of the present disclosure. For the details not disclosed in the embodiments of the apparatus of the present disclosure, please refer to the embodiments of the search result display method based on artificial intelligence described above in the present disclosure.

FIG. 12 schematically illustrates a block diagram of an artificial intelligence based search results presentation apparatus in some embodiments of the present disclosure. As shown in fig. 12, the search result presentation apparatus 1200 may mainly include: a keyword determination module 1210 configured to receive a search request and determine an index keyword according to the search request; the attribute information obtaining module 1220 is configured to retrieve a target brand main body from the brand database according to the index key words, and obtain brand main body attribute information of the target brand main body; a link information acquisition module 1230 configured to determine an application main body and an information dissemination body associated with the target brand main body, and acquire program main body link information corresponding to the application main body and dissemination body link information corresponding to the information dissemination body; and a presentation page generation module 1240 configured to generate a search result presentation page according to the brand subject attribute information, the program subject link information and the propagation subject link information.

In some embodiments of the disclosure, based on the above embodiments, the keyword determination module includes: the search information acquisition module is configured to acquire search information carried in the search request; the semantic recognition module is configured to perform semantic recognition on the search information to obtain basic keywords in the search information; and the keyword expansion module is configured to acquire expanded keywords related to the basic keywords and determine the basic keywords and the expanded keywords as index keywords.

In some embodiments of the present disclosure, based on the above embodiments, the attribute information acquisition module includes: the candidate brand retrieval module is configured to retrieve a plurality of candidate brand main bodies from the brand database according to the index key words; the recommendation information acquisition module is configured to determine an information dissemination subject associated with the candidate brand subject and acquire brand recommendation information corresponding to the information dissemination subject; a target brand determination module configured to select one or more candidate brand principals as target brand principals according to the brand recommendation information.

In some embodiments of the present disclosure, based on the above embodiments, the attribute information acquisition module includes: the candidate brand retrieval module is configured to retrieve a plurality of candidate brand main bodies from the brand database according to the index key words; an information dissemination body determination module configured to determine an information dissemination body associated with the candidate brand body and acquire an exposure rate, an associated user number, and category information of the information dissemination body; a recommendation coefficient determination module configured to determine a brand recommendation coefficient of the information dissemination subject according to the exposure rate, the number of associated users, and the category information; and the target brand determining module is configured to rank the plurality of candidate brand subjects according to the brand recommendation coefficient and determine the target brand subject according to the ranked candidate brand subjects.

In some embodiments of the present disclosure, based on the above embodiments, the index keywords include brand principal index keywords and application index keywords; the attribute information acquisition module includes: a brand recall module configured to retrieve a brand recall keyword of a brand principal in a brand database using the brand principal index keyword; a candidate brand determination module configured to determine a brand principal for which the brand recall keyword matches the brand principal index keyword as a candidate brand principal and determine a candidate application principal associated with the candidate brand principal; a program recall module configured to retrieve an application recall keyword of a candidate application subject in a brand database using the application index keyword; and the brand matching module is configured to determine a candidate application program main body of which the application recall keyword is matched with the application index keyword as a target application program main body and determine a candidate brand main body associated with the target application program main body as a target brand main body.

In some embodiments of the present disclosure, based on the above embodiments, the search result presentation apparatus further includes: the target service item determining module is configured to determine a target service item provided by the target application program main body according to the application program recall keyword and acquire service item link information corresponding to the target service item; the display page generation module is configured to generate a search result display page according to the brand main body attribute information, the program main body link information and the propagation main body link information and in combination with the service item link information.

In some embodiments of the present disclosure, based on the above embodiments, the search result presentation apparatus further includes: a recommended service item determination module configured to determine a recommended service item provided by the application main body and acquire service item link information corresponding to the recommended service item; the display page generation module is configured to generate a search result display page according to the brand main body attribute information, the program main body link information and the propagation main body link information and in combination with the service item link information.

It should be noted that the computer system 1300 of the electronic device shown in fig. 13 is only an example, and should not bring any limitation to the functions and the scope of the application of the embodiments of the present disclosure.

As shown in fig. 13, a computer system 1300 includes a Central Processing Unit (CPU)1301 that can perform various appropriate actions and processes according to a program stored in a Read-Only Memory (ROM) 1302 or a program loaded from a storage section 1308 into a Random Access Memory (RAM) 1303. In the RAM 1303, various programs and data necessary for system operation are also stored. The CPU1301, the ROM 1302, and the RAM 1303 are connected to each other via a bus 1304. An Input/Output (I/O) interface 1305 is also connected to bus 1304.

The following components are connected to the I/O interface 1305: an input portion 1306 including a keyboard, a mouse, and the like; an output section 1307 including a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, a speaker, and the like; a storage portion 1308 including a hard disk and the like; and a communication section 1309 including a network interface card such as a LAN (Local area network) card, a modem, or the like. The communication section 1309 performs communication processing via a network such as the internet. A drive 1310 is also connected to the I/O interface 1305 as needed. A removable medium 1311 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 1310 as necessary, so that a computer program read out therefrom is mounted into the storage portion 1308 as necessary.

In particular, the processes described in the various method flowcharts may be implemented as computer software programs, according to embodiments of the present disclosure. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such embodiments, the computer program may be downloaded and installed from a network via communications component 1309 and/or installed from removable media 1311. The computer program executes various functions defined in the system of the present application when executed by a Central Processing Unit (CPU) 1301.

It should be noted that the computer readable medium shown in the embodiments of the present disclosure may be a computer readable signal medium or a computer readable storage medium or any combination of the two. 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 of the computer readable storage medium may include, but are not limited to: 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), a 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 present disclosure, 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. In contrast, in the present disclosure, 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, wired, etc., or any suitable combination of the foregoing.

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

It should be noted that although in the above detailed description several modules or units of the device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit, according to embodiments of the present disclosure. Conversely, the features and functions of one module or unit described above may be further divided into embodiments by a plurality of modules or units.

Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which may be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.

Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains.

It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A search result display method based on artificial intelligence is characterized by comprising the following steps:

receiving a search request, and determining an index keyword according to the search request;

searching a target brand main body in a brand database according to the index key words, and acquiring brand main body attribute information of the target brand main body;

determining an application program main body and an information dissemination main body which are associated with the target brand main body, and acquiring program main body link information corresponding to the application program main body and dissemination main body link information corresponding to the information dissemination main body;

and generating a search result display page according to the brand main body attribute information, the program main body link information and the propagation main body link information.

2. The artificial intelligence based search result presentation method of claim 1, wherein the determining index keywords according to the search request comprises:

acquiring search information carried in the search request;

performing semantic recognition on the search information to obtain basic keywords in the search information;

and acquiring expanded keywords related to the basic keywords, and determining the basic keywords and the expanded keywords as index keywords.

3. The artificial intelligence based search result presentation method of claim 1, wherein the retrieving a target brand main body in a brand database according to the index key word comprises: searching a plurality of candidate brand main bodies in a brand database according to the index key words;

determining an information dissemination subject associated with the candidate brand subject, and acquiring brand recommendation information corresponding to the information dissemination subject;

one or more candidate brand subjects are selected as target brand subjects according to the brand recommendation information.

4. The artificial intelligence based search result presentation method of claim 1, wherein the retrieving a target brand main body in a brand database according to the index key word comprises:

searching a plurality of candidate brand main bodies in a brand database according to the index key words;

determining an information dissemination main body associated with the candidate brand main body, and acquiring the exposure rate, the number of associated users and category information of the information dissemination main body;

determining a brand recommendation coefficient of the information dissemination main body according to the exposure rate, the number of associated users and the category information;

and sequencing the candidate brand subjects according to the brand recommendation coefficient, and determining a target brand subject according to the sequenced candidate brand subjects.

5. The artificial intelligence based search result presentation method of claim 1, wherein the index keywords comprise brand subject index keywords and application index keywords; the step of retrieving a target brand main body in a brand database according to the index key words comprises the following steps:

retrieving a brand recall keyword of a brand principal in a brand database by using the brand principal index keyword;

determining a brand principal for which the brand recall keyword matches the brand principal index keyword as a candidate brand principal, and determining a candidate application principal associated with the candidate brand principal;

searching an application recall keyword of the candidate application main body in a brand database by using the application index keyword;

and determining a candidate application program main body of which the application recall keyword is matched with the application index keyword as a target application program main body, and determining a candidate brand main body associated with the target application program main body as a target brand main body.

6. The artificial intelligence based search result presentation method of claim 5,

the method further comprises the following steps: determining a target service item provided by the target application program main body according to the application program recall keyword, and acquiring service item connection information corresponding to the target service item;

generating a search result display page according to the brand subject attribute information, the program subject link information and the propagation subject link information, including:

and generating a search result display page according to the brand main body attribute information, the program main body link information and the propagation main body link information and in combination with the service item link information.

7. The artificial intelligence based search result presentation method of claim 1, further comprising: determining a recommended service item provided by the application program main body, and acquiring service item connection information corresponding to the recommended service item;

8. A search result presentation apparatus based on artificial intelligence, comprising:

the keyword determining module is configured to receive a search request and determine an index keyword according to the search request;

the attribute information acquisition module is configured to retrieve a target brand main body from a brand database according to the index key words and acquire brand main body attribute information of the target brand main body;

a link information acquisition module configured to determine an application program main body and an information dissemination main body associated with the target brand main body, and acquire program main body link information corresponding to the application program main body and dissemination main body link information corresponding to the information dissemination main body;

and the display page generating module is configured to generate a search result display page according to the brand main body attribute information, the program main body link information and the propagation main body link information.

9. A computer-readable medium, on which a computer program is stored, which, when being executed by a processor, carries out the artificial intelligence based search result presentation method of any one of claims 1 to 7.

10. An electronic device, comprising:

a processor; and

a memory for storing executable instructions of the processor;

wherein the processor is configured to perform the artificial intelligence based search result presentation method of any of claims 1-7 via execution of the executable instructions.