WO2016107326A1

WO2016107326A1 - Search recommending method and device based on search terms

Info

Publication number: WO2016107326A1
Application number: PCT/CN2015/095016
Authority: WO
Inventors: 龚颖坤; 项碧波; 董毅
Original assignee: 北京奇虎科技有限公司; 奇智软件（北京）有限公司
Priority date: 2014-12-30
Filing date: 2015-11-19
Publication date: 2016-07-07
Also published as: CN104699751A

Abstract

Disclosed are a search recommending method and device based on search terms. The method comprises: constructing an anonymous behavior network topology according to an anonymous search log; and selecting recommendation results related to search terms from the anonymous behavior network topology in response to an event of inputting the search terms by a user. According to the technical solution provided by the present invention, extension is performed on the basis of user behaviors, minority dimensions that the users are most concerned with are mined deeply, the defect that the recommendation results are excessively generalized in the prior art is eliminated, the recommendation results are divided through clustering, each class is accurately described by using knowledge graphs, and valuable information is provided, so that the selected recommendation results better conform to search habits and search demands of the users.

Description

Method and device for searching recommendation based on search words

Technical field

The present invention relates to the field of Internet technologies, and in particular, to a method and apparatus for performing search recommendation based on search terms.

Background technique

With the continuous development of Web technology, the creation and sharing of Internet information has become easier and easier. The extreme explosion of information has made it more and more difficult for people to find the information they need. Search recommendation technology came into being, search recommendation technology The point is to guide users to find the information and information they need more quickly and accurately.

The existing search recommendation descriptions are generally referred to as "related xx", where xx is a category with no information, such as "person", "movie", etc., and the recommendation results of different categories are mixed together; for example, at present There is a search engine searching for "Transformers", and the search engine will appear to recommend "related characters", which include both movie actors and comic characters. The recommendation results of each dimension are mixed together, making it difficult for users to distinguish and find, and the user experience is more difference.

Not only that, the existing search recommendations are mostly based on Collaborative Filtering or Association Rules, which is characterized by a small number of results and insufficient focus, which leads to the recommendation results and user intent. For example, in the existing search engine search for "Jiuzhaigou", the search engine will appear "relevant attractions" recommendation, basically some of the national hot spots with little relationship with "Jiuzhaigou", such search recommendation scheme does not meet the user's search needs, It makes little sense to the user.

Summary of the invention

In view of the above problems, the present invention has been made in order to provide a method and apparatus for performing search recommendation based on search terms that overcomes the above problems or at least partially solves the above problems.

According to an aspect of the present invention, a method for performing search recommendation based on a search term is provided, the method comprising:

Construct an anonymous behavior network topology based on anonymous search logs;

In response to the user entering an event of the search term, a recommendation result associated with the search term is selected from the anonymous behavioral network topology.

According to another aspect of the present invention, an apparatus for performing search recommendation based on a search term is provided, the apparatus comprising:

a building unit adapted to construct an anonymous behavior network topology based on anonymous search logs;

The recommendation unit is adapted to select a recommendation result related to the search term from the anonymous behavior network topology in response to an event of the user inputting the search term.

According to still another aspect of the present invention, a computer program is provided, comprising computer readable code, when said computer readable code is run on a computing device, causing said computing device to perform said search term based on said Search for recommended methods.

According to still another aspect of the present invention, a computer readable medium is proposed, wherein the computer program described above is stored.

It can be seen from the above that the technical solution provided by the present invention completes the process of searching and recommending based on the search term by constructing an anonymous behavior network topology and selecting a recommendation result related to the search term input by the user. Because the anonymous behavior network topology reflects the behavior rules of the user in the statistical sense, the selected recommendation results are more in line with the user's search habits and search requirements.

The above description is only an overview of the technical solutions of the present invention, and the above-described and other objects, features and advantages of the present invention can be more clearly understood. Specific embodiments of the invention are set forth below.

DRAWINGS

Various other advantages and benefits will become apparent to those skilled in the art from a The drawings are only for the purpose of illustrating the preferred embodiments and are not to be construed as limiting. Throughout the drawings, the same reference numerals are used to refer to the same parts. In the drawing:

1 shows a flow chart of a method for performing search recommendations based on search terms, in accordance with one embodiment of the present invention;

2 shows a schematic diagram of an apparatus for performing search recommendations based on search terms, in accordance with one embodiment of the present invention;

3 is a schematic diagram of another apparatus for performing search recommendation based on search terms according to another embodiment of the present invention;

4A shows a schematic diagram of a search result page in accordance with one embodiment of the present invention;

4B shows a schematic diagram of a search result page in accordance with another embodiment of the present invention;

Figure 5 shows schematically a block diagram of a computing device for performing the method according to the invention;

Fig. 6 schematically shows a storage unit for holding or carrying program code implementing the method according to the invention.

Specific embodiment

Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While the embodiments of the present invention have been shown in the drawings, the embodiments Rather, these embodiments are provided so that this disclosure will be more fully understood and the scope of the disclosure will be fully disclosed.

1 shows a flow chart of a method for performing search recommendations based on search terms, in accordance with one embodiment of the present invention. As shown in Figure 1, the method includes:

Step S110, constructing an anonymous behavior network topology according to the anonymous search log.

In the embodiment of the present invention, an anonymous search log is used as a data source, and different methods can be used to construct an anonymous behavior network topology. The anonymous behavioral network topology built is capable of correlating the common interests of most users.

In step S120, in response to the user inputting the event of the search term, the recommendation result related to the search term is selected from the anonymous behavior network topology.

It can be seen that the method shown in FIG. 1 completes the process of searching and recommending based on the search term by constructing an anonymous behavior network topology and selecting a recommendation result related to the search term input by the user. Because the anonymous behavior network topology reflects the behavior rules of the user in the statistical sense, the selected recommendation results are more in line with the user's search habits and search requirements.

In an embodiment of the present invention, the method shown in FIG. 1 further includes: clustering the recommendation results to obtain a plurality of classes, and sorting the plurality of classes.

The above clustering of the recommendation results means that the recommendation results with the same dimension are clustered together; sorting the multiple classes means: by using some rules, such as correlation or search heat, benchmarking multiple classes Sort. For example, the search term entered by the user is “Transformers”, and the recommended results selected from the anonymous behavior network topology include: “Megatron”, “Falling King Kong”, “Megen Fox”, “The Milky Way of Transformers” Force", "Rickel Taylor", "Transformers" "Carman's War", etc., among them, "Megatron" and "Falling King Kong" are the characters of Transformers, "Megen Fox" and "Rickel Taylor" are all participating in the "Transformers" movie. Starring, "The Power of the Transformers" and "The Transformers of the Transformers" are all science fiction films related to Transformers. Therefore, clustering the above recommended results yields three categories: the role of Transformers, starring "Deformation" King Kong's actors and Transformers-related sci-fi films. Sort the three based on relevance and search heat.

In order to ensure the purity of the recommendation result, in an embodiment of the present invention, before clustering the recommendation result, the method shown in FIG. 1 further includes: filtering the recommendation result, filtering out the ambiguous and belonging to the spam content. Recommended results, get filtered recommendations. Then, the filtered recommendation results are clustered to obtain multiple classes, and multiple classes are sorted.

Further, in an embodiment of the present invention, after sorting the plurality of classes, the method further comprises: selecting an appropriate description for each class as the name of the class according to the knowledge map.

When different users search for the same content, the search terms are different. The knowledge map focuses on exploring the attributes of these search words and the connection between them, and connecting different search words with the same search content, so knowledge The map reflects the complete body of knowledge of a content and the appropriate classification and name.

In the above example of user search "Transformers", according to the knowledge map, select an appropriate description for each of the three classes as the name of the class: Transformers character, "Transformers" starring and science fiction film.

According to an embodiment of the present invention, in step S110 of the method shown in FIG. 1, constructing an anonymous behavior network topology according to an anonymous search log includes: using an anonymous user and a search term as a node according to content in the anonymous search log, and Click on the behavior side to build an anonymous behavior network topology. In this way, the search term "Transformers" is found by the click behavior of the A user, and the B user also clicks and searches for "Transformers", then the user can be associated with the B user, and the B user also clicks and searches for the "Transformers of the Autobot Wars". , then you can link to the Transformers related science fiction, and further can be linked to other users who clicked on the search for "Transformers of the Autobots", and so on.

According to an embodiment of the present invention, in step S120 of the method shown in FIG. 1, selecting a recommendation result related to the search term from an anonymous behavior network topology includes: performing randomization in an anonymous behavior network topology according to a random walk algorithm Walk around and select the predetermined number of recommendations that are most relevant to the search term; or, according to Pagerank, Personalized Pagerank, Random Walk with The Restart, or Metapath algorithm selects a predetermined number of recommendation results that are most relevant to the search term from the anonymous behavior network topology. Here, the random walk algorithm and the Pagerank, Personalized Pagerank, Random Walk with Restart, and Metapath algorithms are all prior art, and are not specifically described herein.

Based on the foregoing embodiments, the method shown in FIG. 1 further includes: embedding the recommended result obtained by the final processing into the search result page for output.

4A is a schematic diagram of a search result page according to an embodiment of the present invention. As shown in FIG. 4A, when a user searches for "Transformers", the search result pages are sorted according to relevance and search popularity, showing the above. The three types of recommendations: Transformers characters, "Transformers" starring and science fiction films. Different types of recommendation results are divided and meaningful descriptions are made to meet the search needs of different users.

4B shows a schematic diagram of a search result page in accordance with another embodiment of the present invention. When the user searches for "Jiuzhaigou", according to a certain algorithm, a predetermined number of recommendation results related to "Jiuzhaigou" are selected from the anonymous behavior network topology, and the recommendation results are filtered and clustered to obtain four types of recommendation results: relevant Sichuan attractions Relevant Sichuan cities; related Yunnan attractions and Yunnan cities; national tourist attractions. Sort the categories based on relevance, prioritize the relevant Sichuan attractions, then recommend a slightly divergent Sichuan city, followed by a more divergent nearby tourist city in Yunnan, and finally some other tourist attractions. According to the knowledge map, select an appropriate description for each class as the name of the class, namely: Sichuan attractions, Sichuan cities, Yunnan administrative divisions and tourist attractions, and embed the four types of recommendation results finally processed into the search results page for output. As shown in Figure 4B. In addition to the manners shown in FIGS. 4A and 4B above, the above-mentioned recommendation results may be arranged only on one side of the search result page (such as the right side) according to the category, and the other side of the page is arranged from top to bottom as a common search result. item.

2 shows a schematic diagram of an apparatus for performing search recommendations based on search terms, in accordance with one embodiment of the present invention. As shown in FIG. 2, the apparatus 200 for performing search recommendation based on a search term includes:

The building unit 210 is adapted to construct an anonymous behavior network topology according to the anonymous search log.

The recommendation unit 220 is adapted to select a recommendation result related to the search term from the anonymous behavior network topology in response to the user inputting the event of the search term.

It can be seen that the device shown in FIG. 2 constructs an anonymous behavior network topology by mutual cooperation of each unit, selects a recommendation result related to a search term input by the user, and completes a search based on the search term. Recommended process. Because the anonymous behavior network topology reflects the behavior rules of the user in the statistical sense, the selected recommendation results are more in line with the user's search habits and search requirements.

In an embodiment of the present invention, the constructing unit 210 of the apparatus shown in FIG. 2 is adapted to construct an anonymous behavior network by using an anonymous user and a search term as nodes according to the content in the anonymous search log. Topology.

In an embodiment of the present invention, the recommending unit 220 of the apparatus shown in FIG. 2 is adapted to randomly walk in an anonymous behavior network topology according to a random walk algorithm, and select a predetermined number of recommendation results most relevant to the search term. Or, suitable for selecting a predetermined number of recommendation results most relevant to the search term from the anonymous behavior network topology according to Pagerank, Personalized Pagerank, Random Walk with Restart, or Metapath algorithm.

FIG. 3 illustrates a schematic diagram of another apparatus for performing search recommendations based on search terms, in accordance with another embodiment of the present invention. As shown in FIG. 3, the apparatus 300 for performing search recommendation based on a search term includes: a construction unit 310, a recommendation unit 320, a clustering unit 330, a filtering unit 340, a description adding unit 350, and an output unit 360.

The configuration unit 310 and the recommendation unit 320 are respectively the same as the construction unit 210 and the recommendation unit 220 of the device shown in FIG. 2, and details are not described herein again.

The clustering unit 330 is adapted to cluster the recommendation results obtained by the recommendation unit 320 to obtain a plurality of classes, and sort the plurality of classes.

In an embodiment of the present invention, in order to ensure the purity of the recommendation result, the filtering unit 340 is adapted to filter the recommendation result obtained by the recommendation unit 320, filter out the ambiguous and recommendation results belonging to the spam content, and obtain filtering. The subsequent recommendation result is output to the clustering unit 330.

The description adding unit 350 is adapted to select an appropriate description for each class clustered by the clustering unit 330 as the name of the class according to the knowledge map.

The output unit 360 is adapted to embed the recommended result obtained by the final processing into the search result page for output.

The process performed by the apparatus shown in FIG. 2 and FIG. 3 is described in detail above by taking the case where the user searches for "Transformers" and the case where the user searches for "Jiuzhaigou" as an example, and details are not described herein again.

In summary, the technical solution provided by the present invention expands on the basis of user behavior, constructs an anonymous behavior network topology, and selects a recommendation result related to a search term input by a user by random walk or other algorithm, and completes the search term based on the search term. The process of searching for recommendations. Anonymous behavior network extension In the statistical sense, it reflects the user's behavioral rules for searching, and deeply mines the few dimensions that users pay most attention to, overcomes the shortcomings of the recommendation in the prior art, and uses clustering to divide the recommendation results. Each class is accurately described by the knowledge map, and valuable information is provided, so that the selected recommendation results are more in line with the user's search habits and search requirements.

It should be noted:

The algorithms and displays provided herein are not inherently related to any particular computer, virtual device, or other device. Various general purpose devices can also be used with the teaching based on the teachings herein. The structure required to construct such a device is apparent from the above description. Moreover, the invention is not directed to any particular programming language. It is to be understood that the invention may be embodied in a variety of programming language, and the description of the specific language has been described above in order to disclose the preferred embodiments of the invention.

In the description provided herein, numerous specific details are set forth. However, it is understood that the embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures, and techniques are not shown in detail so as not to obscure the understanding of the description.

Similarly, the various features of the invention are sometimes grouped together into a single embodiment, in the above description of the exemplary embodiments of the invention, Figure, or a description of it. However, the method disclosed is not to be interpreted as reflecting the intention that the claimed invention requires more features than those recited in the claims. Rather, as the following claims reflect, inventive aspects reside in less than all features of the single embodiments disclosed herein. Therefore, the claims following the specific embodiments are hereby explicitly incorporated into the embodiments, and each of the claims as a separate embodiment of the invention.

Those skilled in the art will appreciate that the modules in the devices of the embodiments can be adaptively changed and placed in one or more devices different from the embodiment. The modules or units or components of the embodiments may be combined into one module or unit or component, and further they may be divided into a plurality of sub-modules or sub-units or sub-components. In addition to such features and/or at least some of the processes or units being mutually exclusive, any combination of the features disclosed in the specification, including the accompanying claims, the abstract and the drawings, and any methods so disclosed, or All processes or units of the device are combined. Each feature disclosed in this specification (including the accompanying claims, the abstract and the drawings) may be replaced by alternative features that provide the same, equivalent or similar purpose.

In addition, those skilled in the art will appreciate that, although some embodiments described herein include certain features that are included in other embodiments and not in other features, combinations of features of different embodiments are intended to be within the scope of the present invention. Different embodiments are formed and formed. For example, in the following claims, any one of the claimed embodiments can be used in any combination.

The various component embodiments of the present invention may be implemented in hardware, or in a software module running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that a microprocessor or digital signal processor (DSP) may be used in practice to implement some of some or all of the means for searching for recommendations based on search terms in accordance with embodiments of the present invention. Or all features. The invention can also be implemented as a device or device program (e.g., a computer program and a computer program product) for performing some or all of the methods described herein. Such a program implementing the invention may be stored on a computer readable medium or may be in the form of one or more signals. Such signals may be downloaded from an Internet website, provided on a carrier signal, or provided in any other form.

For example, Figure 5 schematically illustrates a block diagram of a computing device for performing the method in accordance with the present invention. The computing device conventionally includes a processor 510 and a computer program product or computer readable medium in the form of a memory 520. The memory 520 may be an electronic memory such as a flash memory, an EEPROM (Electrically Erasable Programmable Read Only Memory), an EPROM, a hard disk, or a ROM. Memory 520 has a memory space 530 for program code 531 for performing any of the method steps described above. For example, storage space 530 for program code may include various program code 531 for implementing various steps in the above methods, respectively. The program code can be read from or written to one or more computer program products. These computer program products include program code carriers such as hard disks, compact disks (CDs), memory cards or floppy disks. Such computer program products are typically portable or fixed storage units as described with reference to FIG. The storage unit may have storage segments, storage spaces, and the like that are similarly arranged to memory 520 in the computing device of FIG. The program code can be compressed, for example, in an appropriate form. In general, the storage unit comprises computer readable code 531 ' for performing the steps of the method according to the invention, ie code that can be read by a processor such as 510, which when executed by the computing device causes the calculation The device performs the various steps in the methods described above.

It should be noted that the above embodiments illustrate the invention rather than the invention. Limitations are made and those skilled in the art can devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as a limitation. The word "comprising" does not exclude the presence of the elements or steps that are not recited in the claims. The word "a" or "an" The invention can be implemented by means of hardware comprising several distinct elements and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means can be embodied by the same hardware item. The use of the words first, second, and third does not indicate any order. These words can be interpreted as names.

In addition, it should be noted that the language used in the specification has been selected for the purpose of readability and teaching, and is not intended to be construed or limited. Therefore, many modifications and changes will be apparent to those skilled in the art without departing from the scope of the invention. The disclosure of the present invention is intended to be illustrative, and not restrictive, and the scope of the invention is defined by the appended claims.

The present invention is applicable to computer systems/servers that can operate with numerous other general purpose or special purpose computing system environments or configurations. Examples of well-known computing systems, environments, and/or configurations suitable for use with computer systems/servers include, but are not limited to, personal computer systems, server computer systems, thin clients, thick clients, handheld or laptop devices, based on Microprocessor systems, set-top boxes, programmable consumer electronics, networked personal computers, small computer systems, mainframe computer systems, and distributed cloud computing technology environments including any of the above, and the like.

The computer system/server can be described in the general context of computer system executable instructions (such as program modules) being executed by a computer system. Generally, program modules may include routines, programs, target programs, components, logic, data structures, and the like that perform particular tasks or implement particular abstract data types. The computer system/server can be implemented in a distributed cloud computing environment where tasks are performed by remote processing devices that are linked through a communication network. In a distributed cloud computing environment, program modules may be located on a local or remote computing system storage medium including storage devices.

"an embodiment," or "an embodiment," or "an embodiment," In addition, please note that the examples of the words "in one embodiment" are not necessarily all Refers to the same embodiment.

Claims

A method for performing search recommendation based on a search term, wherein the method includes:

Construct an anonymous behavior network topology based on anonymous search logs;

In response to the user entering an event of the search term, a recommendation result associated with the search term is selected from the anonymous behavioral network topology.
The method of claim 1 wherein the method further comprises:

Clustering the recommendation results to obtain a plurality of classes, and sorting the plurality of classes.
A method according to any of claims 1-2, wherein

The constructing an anonymous behavior network topology based on the anonymous search log includes:

According to the content in the anonymous search log, anonymous users and search terms are used as nodes to construct an anonymous behavior network topology with the user's click behavior.
The method of any of claims 1-3, wherein the method further comprises: clustering the recommendation results to obtain a plurality of classes:

Filtering the recommendation result, filtering out the ambiguous and recommendation results belonging to the spam content, and obtaining the filtered recommendation result;

Clustering the filtered recommendation results to obtain multiple classes.
The method of any of claims 1-4, wherein after sorting the plurality of classes, the method further comprises:

Based on the knowledge map, choose an appropriate description for each class as the name of the class.
The method of any of claims 1-5, wherein the extracting the recommendation results related to the search term from the anonymous behavior network topology comprises:

Random walks are performed in the anonymous behavior network topology according to a random walk algorithm, and a predetermined number of recommendation results most relevant to the search term are selected.
The method of any of claims 1-6, wherein the selecting a recommendation result related to the search term from the anonymous behavior network topology comprises:

A predetermined number of recommendation results most relevant to the search term are selected from the anonymous behavior network topology according to Pagerank, Personalized Pagerank, Random Walk with Restart, or Metapath algorithm.
The method of any of claims 1-7, wherein the method further comprises:

The recommended result of the final processing is embedded in the search result page for output.
A device for performing search recommendation based on a search term, wherein the device includes:

a building unit adapted to construct an anonymous behavior network topology based on anonymous search logs;

The recommendation unit is adapted to select a recommendation result related to the search term from the anonymous behavior network topology in response to an event of the user inputting the search term.
The device of claim 9 wherein the device further comprises:

And a clustering unit, configured to cluster the recommended results obtained by the recommending unit to obtain a plurality of classes, and sort the plurality of classes.
A device according to any one of claims 9 to 10, wherein

The constructed unit is adapted to construct an anonymous behavior network topology by using an anonymous user and a search term as nodes according to the content in the anonymous search log.
The device according to any of claims 9-11, wherein the device further comprises: a filtering unit, configured to filter the recommendation result obtained by the recommendation unit, filter out ambiguous and recommendation results belonging to spam, and obtain The filtered recommendation result is output to the clustering unit;
The apparatus of any of claims 9-12, wherein the apparatus further comprises:

The description adding unit is adapted to select an appropriate description as the name of the class for each class obtained by clustering the clustering unit according to the knowledge map.
A device according to claims 9-13, wherein

The recommendation unit is adapted to perform a random walk in the anonymous behavior network topology according to a random walk algorithm, and select a predetermined number of recommendation results that are most relevant to the search term.
A device according to claims 9-14, wherein

The recommendation unit is adapted to select, from the anonymous behavior network topology, a predetermined number of recommendation results most relevant to the search term according to a Pagerank, Personalized Pagerank, Random Walk with Restart, or Metapath algorithm.
The device of any of claims 9-15, wherein the device further comprises:

The output unit is adapted to embed the final result obtained by the final processing into the search result page for output.
A computer program comprising computer readable code causing the computing device to perform a search based on a search term according to any one of claims 1-8 when the computer readable code is run on a computing device Recommended method.
A computer readable medium storing the computer program of claim 17.