CN110597962B

CN110597962B - Search result display method and device, medium and electronic equipment

Info

Publication number: CN110597962B
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: 2023-10-27
Anticipated expiration: 2039-09-23
Also published as: CN110597962A

Abstract

The disclosure provides a search result display method, device, 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 index keywords 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 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 can provide a richer and more visual brand information display effect of rich media for users.

Description

Search result display method and device, medium and electronic equipment

Technical Field

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

Background

With the development of computer and network technologies, branding through the internet and providing users with products and services through the internet have become increasingly a common choice for branding bodies. On this basis, numerous network platforms capable of providing brand propaganda channels and product and service sales channels for brand bodies are derived. For example, a user may find public numbers or applets of various brands through a functional interface provided by the WeChat platform, thereby obtaining products or services provided by the brand body.

However, due to the complexity of the brand network resources and the diversity of brand service forms, users often dope many noise information in the search results when searching for related brands or products, services, and the like through the network platform, and the users need to carefully distinguish and filter layer by layer to find accurate brand bodies. Moreover, even if an exact brand body is found, it is also necessary to jump through multiple layers of web pages or application pages to reach a specific product purchase page or service page. Therefore, how to improve the accuracy and efficiency of brand searching is a current urgent problem.

It should be noted that the information disclosed in the above background section is only for enhancing understanding of the background of the application and thus may include information that does not form the prior art that is already known to those of ordinary skill in the art.

Disclosure of Invention

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

Other features and advantages of the present disclosure will be apparent from the following detailed description, or may be learned in part by the practice of the disclosure.

According to one aspect of the disclosed embodiments, there is provided an artificial intelligence based search result presentation method, the method including: receiving a search request, and determining index keywords 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 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 one aspect of the disclosed embodiments, there is provided an artificial intelligence based search result presentation apparatus, the apparatus comprising: the keyword determination module is configured to receive a search request and determine index keywords according to the search request; the attribute information acquisition module is configured to search a brand database according to the index key words to obtain a target brand main body and acquire brand main body attribute information of the target brand main body; a link information acquisition module configured to determine an application principal and an information dissemination principal associated with the target brand principal, and acquire program principal link information corresponding to the application principal and dissemination principal link information corresponding to the information dissemination principal; and 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.

In some embodiments of the present disclosure, based on the above technical solutions, the keyword determining 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 an expansion keyword related to the basic keyword and determine the basic keyword and the expansion keyword as index keywords.

In some embodiments of the present disclosure, based on the above technical solution, the attribute information obtaining module includes: the candidate brand searching module is configured to search a plurality of candidate brand main bodies in 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 subjects and acquire brand recommendation information corresponding to the information dissemination subject; the target brand determining module is configured to select one or more candidate brand bodies as target brand bodies according to the brand recommendation information.

In some embodiments of the present disclosure, based on the above technical solution, the attribute information obtaining module includes: the candidate brand searching module is configured to search a plurality of candidate brand main bodies in a brand database according to the index key words; an information dissemination subject determination module configured to determine an information dissemination subject associated with the candidate brand subject and to obtain exposure, associated user number, and category information for the information dissemination subject; a recommendation coefficient determination module configured to determine brand recommendation coefficients for the information dissemination subject based on the exposure, the number of associated users, and the category information; the target brand determining module is configured to sort the plurality of candidate brand bodies according to the brand recommendation coefficients, and determine a target brand body according to the sorted candidate brand bodies.

In some embodiments of the present disclosure, based on the above technical solutions, the index keywords include brand body index keywords and application index keywords; the attribute information acquisition module includes: a brand recall module configured to retrieve brand recall keywords for a brand principal in a brand database using the brand principal index keywords; 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 application recall keywords of the candidate application principal in a brand database using the application index keywords; and the brand matching module is configured to determine a candidate application program main body matched with the application program recall key and the application program index key 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 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 association 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 main body link information.

In some embodiments of the present disclosure, based on the above technical solutions, the apparatus further includes: a recommended service item determining module configured to determine a recommended service item provided by the application main body and acquire service item related 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 main body link information.

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

According to an aspect of the embodiments of the present disclosure, there is provided an electronic device including: 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 as in the above technical solution via execution of the executable instructions.

In the technical scheme provided by the embodiment of the disclosure, through establishing the association relationship for the brand main body and the plurality of brand association objects, the related information can be integrated and displayed in the brand information search, the search accuracy and the search efficiency are improved, and meanwhile, a richer and more visual rich-media brand information display effect can be provided for the user, so that the user can acquire the products and services provided by the brand main body more quickly and accurately. In addition, through jointly displaying various associated information, the interference of noise information on a target brand main body can be avoided, and a user can intuitively distinguish a regular brand and an mountain-village brand from multiple dimensions such as brand introduction, small programs, public numbers and the like.

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 disclosure and together with the description, serve to explain the principles of the disclosure. It will be apparent to those of ordinary skill in the art that the drawings in the following description are merely examples of the disclosure and that other drawings may be derived from them without undue effort. In the drawings:

Fig. 1 shows an exemplary system architecture schematic to which the technical solution of the present disclosure 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 illustrates a flowchart of steps for determining index keywords in some embodiments of the present disclosure.

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

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

FIG. 6 schematically illustrates a flowchart of steps for retrieving brand bodies based on multiple keywords in some embodiments of the present disclosure.

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

Fig. 8 schematically shows an interactive interface diagram for presenting search results to a user on a mobile terminal.

FIG. 9 schematically illustrates a data sharing system for preserving brand body related data in some embodiments of the present disclosure.

Fig. 10 schematically illustrates the constituent structure of a block chain in some embodiments of the present disclosure.

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

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

Fig. 13 shows a schematic diagram of a computer system suitable for use in implementing embodiments of the present disclosure.

Detailed Description

Example embodiments will now be described more fully with reference to the accompanying drawings. However, the exemplary embodiments may be embodied in many 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 the 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 disclosed aspects may be practiced without one or more of the specific details, or with other methods, components, devices, steps, etc. In other instances, well-known methods, devices, implementations, or operations are not shown or described in detail to avoid obscuring aspects of the disclosure.

The block diagrams depicted in the figures are merely functional entities and do not necessarily correspond to physically separate entities. That is, the functional entities may be implemented in software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor devices and/or microcontroller devices.

The flow diagrams depicted in the figures are exemplary only, and do not necessarily include all of the elements and operations/steps, nor must they 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 order of actual execution may be changed according to actual situations.

In the related art of the present disclosure, a brand body may perform activities such as brand promotion or product sales using a self-developed network platform or by means of a third party network platform. For example, a brand body may construct an official website or a network mall by itself, or may set up a social account number, an application program, an online store, etc. on a third party network platform such as WeChat, microblog, taobao, jindong mall, etc. Taking the WeChat platform as an example, a brand body may run and maintain public numbers or applets for advertising or providing products and services. However, the search of public numbers or applets is generally based on the names and descriptive contents of related subjects, so the search results are also quite cumbersome and various noise information exists. Moreover, simple names and descriptions often do not accurately describe the public number or core functionality of the applet itself. This will result in the user failing to obtain the exposure of the public number or applet that is more relevant to the search term when searching for the application service, and thus the user failing to quickly and accurately find the desired product or service. In addition, in the aspect of display, the search result of the public number or the applet cannot provide a concise direct service for the user, and the user needs to perform multi-layer jump inside the public number or the applet to obtain a specific product or service.

Based on the problems of the above schemes, the present disclosure provides an artificial intelligence based search result display method, an artificial intelligence based search result display device, a computer readable medium and an electronic device capable of providing accurate recall and service through functions.

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, a desktop computer, and the like. 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 a communication link between client 110 and server 130, such as a wired communication link, a wireless communication link, and the like.

The system architecture in 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 composed 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 limited in particular in this disclosure.

For example, when the artificial intelligence-based search result display method provided in the embodiments of the present disclosure is applied to the server 130, a user may fill in search information related to brands, products or services and other contents 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 may perform semantic analysis on information carried in the search request in response to the received search request to obtain a corresponding index keyword, then determine a target brand body, an application program body and an information propagation body associated with the target brand body by using the index keyword, and finally generate a search result display page according to the brand body attribute information, the program body link information and the propagation 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 then presents the rendered page data on the display interface.

In some optional embodiments, an AI processing function module based on artificial intelligence (Artificial Intelligence, AI) may be further provided on the server 130, and the method steps of obtaining the index keyword, determining the target brand body and the like are implemented by using technologies such as voice technology, natural language processing, machine learning and the like.

Artificial intelligence is the theory, method, technique and application system that uses a digital computer or a digital computer-controlled machine to simulate, extend and expand human intelligence, sense the environment, acquire knowledge and use the knowledge to obtain optimal results. In other words, artificial intelligence is an integrated technology of computer science that attempts to understand the essence of intelligence and to produce a new intelligent machine that can react in a similar way to human intelligence. Artificial intelligence, i.e. research on design principles and implementation methods of various intelligent machines, enables the machines to have functions of sensing, reasoning and decision.

The artificial intelligence technology is a comprehensive subject, and relates to the technology with wide fields, namely the technology with a hardware level and the technology with a software level. Artificial intelligence infrastructure technologies generally include 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 other directions.

Key technologies to speech technology (Speech Technology, ST) are automatic speech recognition technology (ASR) and speech synthesis technology (TTS) and voiceprint recognition technology. The method can enable the computer to listen, watch, say and feel, is the development direction of human-computer interaction in the future, and voice becomes one of the best human-computer interaction modes in the future.

Natural language processing (Nature Language processing, NLP) is an important direction in the fields of computer science and artificial intelligence. It is studying various theories and methods that enable effective communication between a person and a computer in natural language. Natural language processing is a science that integrates linguistics, computer science, and mathematics. Thus, the research in this field will involve natural language, i.e. language that people use daily, so it has a close relationship with the research in linguistics. Natural language processing techniques typically include text processing, semantic understanding, machine translation, robotic questions and answers, knowledge graph techniques, and the like.

Machine Learning (ML) is a multi-domain interdisciplinary, involving multiple disciplines such as probability theory, statistics, approximation theory, convex analysis, algorithm complexity theory, etc. It is specially studied how a computer simulates or implements learning behavior of a human to acquire new knowledge or skills, and reorganizes existing knowledge structures to continuously improve own performance. Machine learning is the core of artificial intelligence, a fundamental approach to letting computers have intelligence, which is applied throughout various areas of artificial intelligence. Machine learning and deep learning typically include techniques such as artificial neural networks, confidence networks, reinforcement learning, transfer learning, induction learning, teaching learning, and the like.

Detailed descriptions of the artificial intelligence based search result display method, the artificial intelligence based search result display device, the computer readable medium and the electronic device provided by the present disclosure are provided below in connection with the 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 steps of:

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

The search request may be generated by a client program or web page according to the search needs of the user. After receiving the search request, the client device or the server device may determine the corresponding index keyword. The index keyword may be a keyword related to contents such as brand names, commodity names, 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 according to information input by the user, or may be a keyword automatically generated by clicking or selecting a label or option provided by the search interface under the search interface. For example, the index key may be "express," "Chinese move," "Maban," or the like.

And S220, searching in a brand database according to the index key words to obtain a target brand main body, and acquiring brand main body attribute information of the target brand main body.

To improve accuracy of brand information searching, embodiments of the present disclosure may pre-configure and maintain a brand database for storing introduction information of various brand subjects and network acquisition interfaces of various products or services related to the brand subjects. Each brand body may configure and manage itself-related material and associated information itself, which may include, for example, product listings, product purchase links, service listings, service information, weChat public numbers, weChat applets, and the like. The brand database may uniformly maintain the search elements of each brand body, and the search elements of each brand body may be compared according to the index keyword obtained in step S210, and the brand body that is successfully compared is the target brand body. For the target brand body obtained through retrieval, the brand body attribute information is acquired in the step. The brand body attribute information may include mainly one or more of a brand body name, a brand body identification, a brand body introduction, and a brand authentication identification. The brand body name may be a common name or nickname of the brand body, such as "chinese move", "10086", "chinese move 10086", and so forth. The brand body identifier may be identifying information such as a brand name, LOGO, etc. The brand body introduction may be descriptive text related to the brand body's services, products, etc. The brand authentication mark may be authentication mark information of the nature or attribute of the brand main body, for example, information such as comprehensive exposure rate, number of vermicelli and category may be analyzed on public numbers accessed to the brand search, 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 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.

For the target brand body determined in step S220, the present step may determine one or more brand-related objects associated with the target brand body according to association relationships of each brand body with various related objects. The brand association object may include at least an information dissemination body for disseminating brand information and an application body for providing brand services, and may further include a set of products or service items provided by the brand body. The brand body may manage and maintain a collection of products for presentation in the search results itself, e.g., a cell phone brand may group up-to-date cell phone products into a collection of products. The associated object presentation information corresponding to the product set may include names, models, images, prices, purchase links, etc. of the respective products in the product set. The information dissemination entity 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 or a microblog account, or may be a group broadcasting subject such as a WeChat public number or a Payment Bao life number. The information transmission page provided by the information transmission body can be directly jumped to by using the transmission body link information, for example, a public number page corresponding to the target brand body can be jumped to. The application may be a program client or a WeChat applet for providing branding services, or the like. The corresponding application program main body can be directly opened by using the application program 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 body 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 body. And the presentation content in each search entry may include at least three parts, namely, brand body attribute information, program body link information, and propagation body link information, which are related to the target brand body.

According to the artificial intelligence based search result display method, the association relation is established for the brand main body, the application program main body, the information transmission main body and other brand association objects, related information can be integrated and displayed in brand information search, search accuracy and search efficiency are improved, meanwhile, a richer and more visual rich type brand information display effect can be provided for a user, and the user can acquire products and services provided by the brand main body more quickly and accurately. In addition, through jointly displaying various associated information, the interference of noise information on a target brand main body can be avoided, and a user can intuitively distinguish a regular brand and an mountain-village brand from multiple dimensions such as brand introduction, small programs, public numbers and the like.

FIG. 3 schematically illustrates a flowchart of steps for determining index keywords in some embodiments of the present disclosure. As shown in fig. 3, on the basis of the above embodiment, determining the index keyword according to the search request in step S210 may include the steps of:

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

The user may input the search information on the client device using voice, text, or gesture interaction, etc., and then the client sends a search request generated according to the search information to the server, or the server actively obtains the search request from the client. After the server side analyzes the search request, search information carried in the search request can be obtained, and the search information can be expressed as single characters, words formed by one or more characters or sentences formed by a plurality of words. For example, a user inputs information "i want to send express" at a client by using a voice function, and a search request carrying the information is sent to a server and is analyzed and obtained by the server.

And S320, carrying out 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 on the search information, so that basic keywords related to user intention are obtained. The semantic recognition performed in this step may specifically be a named entity recognition method, 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. Semantic recognition of the search information may result in one or more base keywords, the number of which depends on the information content and the specific semantics of the search information.

S330, obtaining an expanded keyword related to the basic keyword, and determining the basic keyword and the expanded keyword as index keywords.

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

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

FIG. 4 schematically illustrates a flowchart of steps for retrieving a target brand body 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 target brand body retrieved from the brand database according to the index keyword in step S220 may include the following steps:

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

The index keyword may be a keyword related to a brand name, or a keyword related to a product name provided by a brand, a service item, or a content such as a service field to which the brand belongs. The index key words are used as search elements to search a plurality of candidate brand bodies in a brand database, and most of the candidate brand bodies are brand bodies with similar names, same service fields or other related characteristics.

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

For each candidate brand body retrieved in step S410, the present step may determine information propagation bodies associated with each candidate brand body, respectively, e.g., public numbers associated with each candidate brand body, respectively. For each information dissemination agent, corresponding brand recommendation information may be pre-configured for it in the brand database, e.g. all public numbers may be divided into official and non-official types of public numbers according to account agent information of the public numbers. Wherein official public numbers have a higher degree of recommendation, whereas non-official public numbers have a relatively lower degree of recommendation.

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

According to brand recommendation information corresponding to the information propagation subject, the plurality of candidate brand subjects obtained through retrieval can be screened, and one or more candidate brand subjects with higher recommendation degree can be selected as target brand subjects.

When an information propagation body such as a public number is in online operation, authentication data is generally required to be submitted to a public number operation platform, and after the public number operation platform is used for auditing related authentication data, the operation body corresponding to the public number can be authenticated. The candidate brand bodies authenticated by the authorities can be preferentially presented to the user as target brand bodies using the authentication result of the public number as brand recommendation information.

FIG. 5 schematically illustrates a flowchart of steps for retrieving a target brand body 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 target brand body retrieved from the brand database according to the index keyword in step S220 may include the following steps:

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

The manner of searching candidate brand bodies is similar to that of the previous embodiment, and will not be described here again.

Step S520, determining information spreading subjects associated with the candidate brand subjects, and acquiring exposure rates, the number of associated users and category information of the information spreading subjects.

Still taking the public number as an example, after determining the public number associated with each candidate brand body, the step may obtain exposure, number of associated users, and category information for each public number. The exposure rate refers to the number of times of displaying the public number in unit time, the number of associated users can be, for example, the number of concerned users of the public number, and the category information can include different public number types such as subscription numbers, service numbers or enterprise WeChat.

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

The brand recommendation coefficients of the information propagation main body can be determined by analyzing the exposure rate, the number of associated users and the category information, for example, the three information can be quantitatively characterized, and then weighting calculation is carried out according to different weights to obtain the brand recommendation coefficients of the information propagation main body.

S540, sorting the plurality of candidate brand bodies according to the brand recommendation coefficients, and determining a target brand body according to the sorted candidate brand bodies.

The plurality of candidate brand bodies may be ranked according to the size of the brand recommendation coefficient, and then the target brand body may be determined according to the ranking result, for example, a plurality of candidate brand bodies ranked first may be directly determined as the target brand body, or a plurality of candidate brand bodies having a brand recommendation coefficient greater than a certain threshold may be determined as the target brand body.

In some embodiments of the present disclosure, the index key used for brand body retrieval may further include a brand body index key and an application index key. When the index key words determined according to the search request are plural, the embodiments of the present disclosure may perform type recognition on the index key words, determine a part of the index key words as brand body index key words, and determine other index key words than the brand body index key words as application index key words. FIG. 6 schematically illustrates a flowchart of steps for retrieving brand bodies based on multiple keywords in some embodiments of the present disclosure. As shown in fig. 6, on the basis of the above embodiments, the target brand body retrieved from the brand database according to the index keyword in step S220 may include the following steps:

And S610, searching brand recall keywords of the brand main body in the brand database by utilizing the brand main body index keywords.

Corresponding brand recall keywords may be configured for each brand body in the brand body database for retrieval recall thereof. The brand recall keywords may be keywords related to the name of the brand body, the product, the service, and the like. The method comprises the steps of firstly, searching and comparing brand recall keywords corresponding to all brand bodies in a brand database by using brand body index keywords to judge whether the brand body index keywords can be successfully matched with the brand recall keywords.

Step S620, determining brand subjects with brand recall keywords matching brand subject index keywords as candidate brand subjects, and determining candidate application subjects associated with the candidate brand subjects.

When a brand recall keyword can be successfully matched with a brand body index keyword, a brand body corresponding to the brand recall keyword may be determined to be a candidate brand body. Meanwhile, the step can determine candidate application program main bodies associated with the candidate brand main bodies according to a pre-configured association relation.

And S630, searching the application recall keywords of the candidate application main body in the brand database by using the application index keywords.

To improve recall accuracy of a brand body, application recall keywords may be configured for an application body associated with the brand body in a brand database. The step compares the application index keywords with the application recall keywords corresponding to each candidate application body to determine whether the application index keywords can be successfully matched with the application recall keywords. In some alternative embodiments, brand recall keywords may be interleaved with application recall keywords, e.g., some keywords may be used as both brand recall keywords and application recall keywords.

Step S640, determining the candidate application program main body with the application program recall key matched with the application program index key 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 can be successfully matched with an application index key, then the candidate application principal corresponding to the application recall key can be determined as the target application principal. Accordingly, a candidate brand body associated with the target application body may be determined as the target brand body.

For example, when two index keywords are determined according to a search request, one of the keywords may be identified as brand index keywords related to brand body names of brand bodies, and the other keyword may be identified as application index keywords related to application bodies. For example, if the user inputs two keywords of "Hua Cheng" and "cell phone" at the same time, the search keyword "Hua Cheng" as the brand index keyword may determine that the brand body is "Hua Cheng" through search comparison, and the search keyword "cell phone" as the application index keyword may determine that the application body associated with the brand body "Hua Cheng" is "Hua Cheng Cheng+Chemicals" through search comparison. The two search keywords hit the brand body and the application program body with the association relationship at the same time, so that the corresponding brand body can be recalled, and further, brand information search results related to the brand body display information and the association object display information are generated. Conversely, if two search keywords cannot hit both the brand body and the application body having the association, then it may be considered that there is no corresponding brand body in the brand database, avoiding providing the user with erroneous or inaccurate search results.

On the basis of retrieving the target brand main body by using the brand index key words and the application index key words, the embodiment of the disclosure can also determine the target service item provided by the target application main body according to the successfully matched application recall key words, and acquire the service item corresponding to the target service item. For example, when the target brand body is "chinese mobile", the target application body associated with the target brand body is "chinese mobile 10086+" applet, and the corresponding target service item may be determined based on the application recall keyword "phone fee" to include a service item related to the keyword "phone fee" provided by the applet, such as "phone fee query", "phone fee recharge", and the like. For the determined target service item, when the search result display page is generated, the service item corresponding to the target service item can be displayed while the brand main body attribute information, the program main body link information and the propagation main body link information are displayed. The service item information can be utilized to jump to the corresponding applet service page, so that the user can directly obtain the service item to be used.

In addition, when only the brand index keyword is included in the index keyword, the embodiment of the present disclosure may acquire a recommended service item provided by an application program main body after determining the application program main body associated with the target brand main body, and acquire service item associated information corresponding to the recommended service item. For example, when the target brand body is "chinese mobile", the target application body associated with the target brand body is "chinese mobile 10086+" applet, and the recommended service items provided by the applet may include preferentially recommended service items provided by the applet such as "traffic inquiry", "recharge payment" and the like. For the determined recommended service item, when the search result display page is generated, the service item corresponding to the recommended service item may be displayed while the brand body attribute information, the program body link information, and the propagation body link information are displayed. According to the embodiment of the invention, the recommended service item can be intelligently determined according to the use habit of the user or the historical use record of the application program main body and other information, so that the convenience of the user in using the relevant service item is improved.

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

FIG. 7 schematically illustrates a framework diagram of a social platform server building a brand retrieval system from merchant uploaded stories. As shown in FIG. 7, merchants 710 may upload material related to their brands to social platform server 720, which may include brand introduction information, and information about public numbers, applets, or other associated objects associated with brand subjects, to enrich the brand presentation. Social platform server 720 may build brand database 730, including at least keyword library 731 and associated material library 732, based on relevant material uploaded by merchant 710 and the associated information. The keyword library 731 stores recall keywords corresponding to brand subjects, and the associated material library 732 stores information of public numbers, applets, or other associated objects associated with brand subjects. Based on brand database 730, brand search system 740 may be established for searching matches to the user's search needs to provide the user with search results that include content such as attribute information, association information, etc. of the brand body.

Fig. 8 schematically shows an interactive interface diagram for presenting search results to a user on a mobile terminal. As shown in fig. 8, when a user needs to query brand information, view content published by public numbers, or use goods or services provided by applets, the social platform may first be logged in on the mobile terminal. Various functional portals such as "circle of friends", "sweep", "search for one" and the like are provided in the interaction interface 810 of the social platform.

The user may enter the search page 820 by clicking "search one 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 in voice form using the search box 821. A search request may be generated on the mobile terminal based on the search information and sent to the social platform server via network communication.

After the received search request is analyzed by the social platform server, index keywords can be determined, then the brand database is searched and matched by utilizing the brand search system, and the search result is returned to the mobile terminal.

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

The brand body display area 831 is used to display brand body attribute information of the brand body, and may include, for example, a brand body name, a brand body identification, a brand body introduction, a brand authentication identification, and the like.

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 body, and mainly may be a service item provided by the application program body; the application body presentation area 8322 may be used to present an application associated with the brand body, e.g., may present a program jump portal corresponding to a program client jump link or applet jump link; the information dissemination body display area 8323 may be used to display a public broadcast body or a group broadcast body associated with the brand body, for example, may display a page hop entry corresponding to a public number hop link or a corporate hop link.

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

In some embodiments of the present disclosure, various data in a brand database, brand body information, brand-related object information, and the like may be shared stored using blockchain techniques. FIG. 9 schematically illustrates a data sharing system for preserving brand body related data 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, where the data sharing system may include a plurality of nodes 910, and the plurality of nodes 910 may be respective clients in the data sharing system. Each node 910 may receive input information during normal operation and maintain shared data within the data sharing system based on the received input information. In order to ensure the information intercommunication in the data sharing system, information connection can exist between each node in the data sharing system, and the nodes can transmit information through the information connection. For example, when any 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 the shared data, so that the data stored on all nodes in the data sharing system are consistent.

Each node in the data sharing system has a node identifier corresponding to the node identifier, and each node in the data sharing system can store the node identifiers of other nodes in the data sharing system, so that the generated block can be broadcast to other nodes in the data sharing system according to the node identifiers of other nodes. Each node can maintain a node identification list shown in the following table, and the node names and the node identifications are correspondingly stored in the node identification list. The node identifier may be an IP (Internet Protocol, protocol of interconnection between networks) address, and any other information that can be used to identify the node, and the IP address is only illustrated in table 1.

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 and the same blockchain. The blockchain is made up of a plurality of blocks, and fig. 10 schematically illustrates the constituent structure of the blockchain in some embodiments of the present disclosure. As shown in fig. 10, the blockchain 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 characteristic value, a version number, a time stamp and a difficulty value, and the block body stores input information; the next block of the starting block takes the starting block as a father 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 father 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 are associated with the block data stored in the father block, and the safety of the input information in the block is ensured.

FIG. 11 schematically illustrates a process of generating a block from a blockchain in some embodiments of the present disclosure. As shown in fig. 11, when receiving input information, a node where the blockchain is located checks the input information, stores the input information into a memory pool after the check is completed, and updates a hash tree used for recording the input information; then, updating the update time stamp to the time of receiving the input information, trying different random numbers, and calculating the characteristic value for a plurality of 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 eigenvalue algorithm used to calculate eigenvalues; version (version number) is version information of the related block protocol in the block chain; the prev_hash is the block header characteristic value of the parent block of the current block; the merkle_root is a characteristic value of input information; ntime is the update time of the update timestamp; the nbits is the current difficulty, is a fixed value in a period of time, and is determined again after exceeding a fixed period of time; x is a random number; TARGET is a eigenvalue threshold that can be determined from nbits.

Thus, when the random number meeting the formula is calculated, the information can be correspondingly stored to generate the block head and the block main body, and the current block is obtained. And then, the node where the blockchain is located sends the newly generated blocks to other nodes in the data sharing system where the newly generated blocks are located according to the node identification of other nodes in the data sharing system, the other nodes verify the newly generated blocks, and the newly generated blocks are added into the blockchain stored in the newly generated blocks after the verification is completed.

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

The following describes embodiments of the apparatus of the present disclosure that may be used to perform the artificial intelligence based search result presentation methods of the above embodiments of the present disclosure. For 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 in the present disclosure.

FIG. 12 schematically illustrates a block diagram of an artificial intelligence based search result 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 index keywords according to the search request; an attribute information obtaining module 1220 configured to retrieve the target brand body from the brand database according to the index key, and obtain brand body attribute information of the target brand body; a link information acquisition module 1230 configured to determine an application principal and an information dissemination principal associated with a target brand principal, and acquire program principal link information corresponding to the application principal and dissemination principal link information corresponding to the information dissemination principal; the presentation page generation module 1240 is configured to generate a search result presentation page according to the brand body attribute information, the program body link information, and the propagation body link information.

In some embodiments of the present disclosure, based on the above embodiments, the keyword determination module includes: the search information acquisition module is configured to acquire search information carried in a 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 an expansion keyword related to the basic keyword and determine the basic keyword and the expansion keyword as index keywords.

In some embodiments of the present disclosure, based on the above embodiments, the attribute information acquisition module includes: the candidate brand searching module is configured to search a plurality of candidate brand main bodies in the brand database according to the index key words; a recommended information acquisition module configured to determine an information dissemination subject associated with the candidate brand subjects and acquire brand recommended information corresponding to the information dissemination subject; the target brand determination module is configured to select one or more candidate brand bodies as target brand bodies 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 searching module is configured to search a plurality of candidate brand main bodies in the brand database according to the index key words; an information dissemination subject determination module configured to determine an information dissemination subject associated with a candidate brand subject and to obtain exposure, number of associated users, and category information for the information dissemination subject; the recommendation coefficient determining module is configured to determine brand recommendation coefficients of the information spreading main body according to the exposure rate, the number of associated users and the category information; the target brand determining module is configured to rank the plurality of candidate brand bodies according to the brand recommendation coefficients and determine the target brand bodies according to the ranked candidate brand bodies.

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

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 a 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 brand main body attribute information, program main body link information and propagation main body link information and by combining service main body 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 determining module configured to determine a recommended service item provided by the application main body and acquire service item associated information corresponding to the recommended service item; the display page generation module is configured to generate a search result display page according to brand main body attribute information, program main body link information and propagation main body link information and by combining service main body 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 impose any limitation on the functions and the application scope of the embodiments of the present disclosure.

As shown in fig. 13, the computer system 1300 includes a central processing unit (Central Processing Unit, CPU) 1301, which 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 portion 1308 into a random access Memory (Random Access Memory, RAM) 1303. In the RAM 1303, various programs and data required for the system operation are also stored. The CPU 1301, ROM 1302, and RAM 1303 are connected to each other through 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 section 1306 including a keyboard, a mouse, and the like; an output portion 1307 including a Cathode Ray Tube (CRT), a liquid crystal display (Liquid Crystal Display, LCD), and the like, a speaker, and the like; a storage portion 1308 including a hard disk or 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 a communication process via a network such as the internet. The drive 1310 is also connected to the I/O interface 1305 as needed. Removable media 1311, such as magnetic disks, optical disks, magneto-optical disks, semiconductor memory, and the like, is installed as needed on drive 1310 so that a computer program read therefrom is installed as needed into storage portion 1308.

In particular, according to embodiments of the present disclosure, the processes described in the various method flowcharts may be implemented as computer software programs. 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 shown in the flowcharts. In such embodiments, the computer program may be downloaded and installed from a network via the communication portion 1309 and/or installed from the removable medium 1311. When executed by a Central Processing Unit (CPU) 1301, performs various functions defined in the system of the present application.

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. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any 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 (Erasable Programmable Read Only Memory, EPROM), 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 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 the present disclosure, however, the computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with the computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. 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 flowcharts 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 a 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 in accordance with embodiments of the present disclosure. Conversely, the features and functions of one module or unit described above may be further divided into a plurality of modules or units to be embodied.

From the above description of embodiments, those skilled in the art will readily appreciate that the example embodiments described herein may be implemented in software, or may be implemented in software in combination with the necessary hardware. Thus, 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 (may be a CD-ROM, a U-disk, a mobile hard disk, etc.) or on a network, and includes several instructions to cause a computing device (may be a personal computer, a server, a touch terminal, or a network device, etc.) to perform 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 adaptations, 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 is to be understood that the present disclosure is not limited to the precise arrangements and instrumentalities shown in the drawings, and that various modifications and changes may be effected without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. An artificial intelligence based search result display method, which is characterized by comprising the following steps:

receiving a search request, and determining index keywords according to the search request; the index keywords comprise brand index keywords and application index keywords;

searching brand recall keywords of the brand in a brand database by utilizing the brand index keywords;

determining that a brand of the brand recall keyword matches the brand index keyword as a candidate brand, and determining a candidate application associated with the candidate brand;

searching the application recall keywords of the candidate application in a brand database by utilizing the application index keywords;

determining a candidate application program with the application program recall key word matched with the application program index key word as a target application program, determining a candidate brand associated with the target application program as a target brand, and acquiring brand attribute information of the target brand;

determining an application program and an information dissemination subject associated with the target brand, and acquiring program subject link information corresponding to the application program and dissemination subject link information corresponding to the information dissemination subject; the information dissemination subject is a network information dissemination interface or channel for disseminating brand information;

And generating a search result display page according to the brand 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;

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

and acquiring an extended keyword related to the basic keyword, and determining the basic keyword and the extended keyword as index keywords.

3. The artificial intelligence based search result presentation method of claim 1, further comprising:

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

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

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

4. The artificial intelligence based search result presentation method of claim 1, further comprising:

determining information spreading subjects associated with the candidate brands, and acquiring exposure rates, the number of associated users and category information of the information spreading subjects;

determining brand recommendation coefficients of the information spreading main body according to the exposure rate, the number of associated users and the category information;

and sorting the candidate brands according to the brand recommendation coefficients, and determining a target brand according to the sorted candidate brands.

5. The artificial intelligence based search result presentation method of claim 1, further comprising: determining a target service item provided by the target application program according to the application program recall keyword, and acquiring service chain information corresponding to the target service item;

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

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

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

7. An artificial intelligence based search result presentation apparatus, comprising:

the keyword determination module is configured to receive a search request and determine index keywords according to the search request; the index keywords comprise brand index keywords and application index keywords;

an attribute information acquisition module configured to retrieve brand recall keywords for brands in a brand database using the brand index keywords; determining that a brand of the brand recall keyword matches the brand index keyword as a candidate brand, and determining a candidate application associated with the candidate brand; searching the application recall keywords of the candidate application in a brand database by utilizing the application index keywords; determining a candidate application program with the application program recall key word matched with the application program index key word as a target application program, determining a candidate brand associated with the target application program as a target brand, and acquiring brand attribute information of the target brand;

A link information acquisition module configured to determine an application program and an information dissemination subject associated with the target brand, and acquire program subject link information corresponding to the application program and dissemination subject link information corresponding to the information dissemination subject; the information dissemination subject is a network information dissemination interface or channel for disseminating brand information;

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

8. A computer readable medium having stored thereon a computer program, wherein the computer program when executed by a processor implements the artificial intelligence based search result presentation method of any of claims 1 to 6.

9. 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 one of claims 1 to 6 via execution of the executable instructions.