CN108388630A

CN108388630A - A kind of shopping information method for pushing, device and electronic equipment

Info

Publication number: CN108388630A
Application number: CN201810150212.6A
Authority: CN
Inventors: 彭睿棋
Original assignee: Beijing Qihoo Technology Co Ltd
Current assignee: Beijing Qihoo Technology Co Ltd
Priority date: 2018-02-13
Filing date: 2018-02-13
Publication date: 2018-08-10

Abstract

The present invention discloses a kind of shopping information method for pushing, device and electronic equipment, the search need for class of being done shopping by preposition user when initiating the search of shopping type in user, the search efficiency and user experience of significant increase search engine, personalized search recommendation results are provided, the realization efficiency and user's viscosity of search engine are increased.This method includes：In the search content for detecting target user's search shopping type, the web-based history behavior record of the shopping type of the whole network user is extracted；The web-based history behavior record of shopping type based on the whole network user determines the recommendation information of shopping type corresponding with the target user；The recommendation information of the shopping type is illustrated in result of page searching corresponding with the shopping search content of type.

Description

A kind of shopping information method for pushing, device and electronic equipment

Technical field

The present invention relates to a kind of electronic technology field more particularly to shopping information method for pushing, device and electronic equipments.

Background technology

As the information processing technology develops, more and more electronic equipments appear in the work and life of people, convenient Daily life.These electronic equipments are provided to the user by internet easily to be serviced.The development institute band of internet The information content come increases so that user is increasingly fixed against search engine when filter information.Search engine refers to basis Certain strategy collects information with specific computer program from internet, after carrying out tissue and processing to information, is User provides retrieval service, will search for the system that the relevant information of content shows user with user.Currently, being used in user During search engine, traditional search engine only provides official website addressing service, such as：User searches for the name of certain electric business website Claim, the search result that search engine is determined is the network address of electric business website.Therefore, prior art search engine is only capable of meeting user Web site query demand, the search service provided is single, and user's viscosity is poor.

Invention content

In view of the above problems, it is proposed that the present invention overcoming the above problem in order to provide one kind or solves at least partly State shopping information method for pushing, device and the electronic equipment of problem.

In a first aspect, the application provides a kind of shopping information method for pushing, including：

In the search content for detecting target user's search shopping type, the shopping type of the whole network user is extracted Web-based history behavior record；

The web-based history behavior record of shopping type based on the whole network user, determination are corresponding with the target user The recommendation information for type of doing shopping；

The recommendation information of the shopping type is illustrated in search result corresponding with the shopping search content of type In the page.

Optionally, the web-based history behavior record of the shopping type based on the whole network user determines and the mesh The recommendation information of the corresponding shopping type of user is marked, including：

The web-based history behavior record of shopping type based on the whole network user, determines candidate items；

It determines each scoring of the user to candidate items in the whole network user, establishes user's rating matrix；

Based on the rating matrix, neighbor user collection similar with the target user in the whole network user is determined；

Based on the neighbor user collection, recommended project is determined from the candidate items；

Determine that recommendation information corresponding with the recommended project is the recommendation of type of doing shopping corresponding with the target user Information.

Optionally, the web-based history behavior record for obtaining the whole network user, including：

Obtain the search record of the shopping type of the whole network user in preset time range, the click record of shopping type It is combined with any one or more in the browsing record of shopping type.

Optionally, the web-based history behavior record of the shopping type based on the whole network user, determines candidate item Mesh, including：

Determine that searching times are more than in the search record of the shopping type of the whole network user in the preset time range The search content of first preset times is candidate items；And/or

Determine that the click record midpoint machine number of the shopping type of the whole network user in the preset time range is more than The click on content of second preset times is candidate items；And/or

Determine that number of visits is more than in the browsing record of the shopping type of the whole network user in the preset time range The browsing content of third preset times is candidate items.

Optionally, described to be based on the rating matrix, determine neighbour similar with the target user in the whole network user User's collection is occupied, including：

Based on the rating matrix, the similitude of the target user and other users in the whole network user are calculated；

Based on the similitude of other users in the target user and the whole network user, determine and target user's phase As neighbor user collection.

Optionally, the similitude based on other users in the target user and the whole network user, determining and institute The similar neighbor user collection of target user is stated, including：

Determine similar with target user neighbor user collection include in the whole network user with the target user Similitude is more than the user of the first predetermined threshold value.

Determine similar with target user neighbor user collection include in the whole network user with the target user Similitude arrange from large to small after preceding first preset number user.

Optionally, described to be based on the neighbor user collection, recommended project is determined from the candidate items, including：

Based on the neighbor user collection, determine that the target user is pre- to the interest-degree of each project in the candidate items Measured value；

Determine that the project that interest-degree predicted value is more than the second predetermined threshold value in the candidate items is recommended project or determination The project of preceding second preset number after interest-degree predicted value arranges from large to small in the candidate items is recommended project.

Determine weighted average of all neighbor users to each project in the candidate items of the neighbor user concentration Interest-degree；

Determine that project that weighted average interest-degree in the candidate items is more than third predetermined threshold value is recommended project or really The project of preceding third preset number after weighted average interest-degree arranges from large to small in the fixed candidate items is recommended project.

Optionally, the recommendation information by the shopping type is illustrated in corresponding with the shopping search content of type Result of page searching in, including：

The recommendation information of the shopping type is illustrated under the corresponding search result of search content of the shopping type The recommendation information of side, the shopping type includes candidate search word corresponding with the recommended project and/or web page interlinkage.

Optionally, the search content of the shopping type includes：Shopping website title, shopping website link and trade name In any one or more combine.

Optionally, the recommendation information by the shopping type is illustrated in corresponding with the shopping search content of type Result of page searching, including：

Searching for the shopping type searched for the target user is determined from the recommendation information of the shopping type The relevant recommendation information of rope content；

The relevant recommendation information of search content for the shopping type searched for the target user is illustrated in and institute State the corresponding result of page searching of search content of shopping type.

Optionally, the recommendation information of the shopping type specifically includes user and can directly place an order the merchandise items of purchase, institute The method of stating further includes：

User is responded to the trigger action of the merchandise items, the corresponding purchase webpage of the merchandise items is loaded, for institute It states user and the merchandise items is bought by the purchase webpage.

Second aspect, the application provide a kind of shopping information method for pushing, including：

The web-based history behavior record of shopping type based on the whole network user, determination are similar with the target user Similar users collection；

The information that the interested shopping type of each similar users is concentrated based on the similar users, is determined and the target The recommendation information of the corresponding shopping type of user；

Second aspect, the application provide a kind of shopping information pusher, including：

Acquiring unit, in the search content for detecting target user's search shopping type, extraction the whole network to be used The web-based history behavior record of the shopping type at family；

Determination unit, be used for the shopping type based on the whole network user web-based history behavior record, determination with it is described The recommendation information of the corresponding shopping type of target user；

Display unit, for the recommendation information of the shopping type to be illustrated in the search content pair with the shopping type In the result of page searching answered.

Optionally, the determination unit includes：

First determining module is used for the web-based history behavior record of the shopping type based on the whole network user, determines Candidate items；

Second determining module establishes user for determining each scoring of the user to candidate items in the whole network user Rating matrix；

Third determining module, for be based on the rating matrix, determine in the whole network user with target user's phase As neighbor user collection；

4th determining module determines recommended project for being based on the neighbor user collection from the candidate items；

5th determining module, for determining that recommendation information corresponding with the recommended project is corresponding with the target user Shopping type recommendation information.

Optionally, the acquiring unit is used for：

Optionally, first determining module is used for：

Optionally, the third determining module is used for：

Optionally, the 4th determining module is used for：

Optionally, the display unit is used for：

Optionally, the recommendation information of the shopping type specifically includes user and can directly place an order the merchandise items of purchase, institute Stating device further includes：

Response unit, the trigger action for responding user to the merchandise items, it is corresponding to load the merchandise items Webpage is bought, the merchandise items are bought by the purchase webpage for the user.

Fourth aspect, the application provide a kind of shopping information pusher, including：

First determination unit, be used for the shopping type based on the whole network user web-based history behavior record, determine and The similar similar users collection of the target user；

Second determination unit, the letter for concentrating the interested shopping type of each similar users based on the similar users Breath determines the recommendation information of shopping type corresponding with the target user；

5th aspect, the application provide a kind of electronic equipment, and the electronic equipment includes processor and memory：It is described to deposit Reservoir is used to store the program for the shopping information method for pushing for executing aforementioned first aspect and second aspect；The processor It is configurable for executing the program stored in the memory.

6th aspect, the application provides a kind of computer storage media, for being stored as above-mentioned shopping information pusher Computer software instructions used, it includes be the program designed by shopping information pusher for executing above-mentioned aspect.

Said one in the embodiment of the present application or multiple technical solutions at least have following one or more technology effects Fruit：

In the technical solution of the embodiment of the present invention, in the search content situation for detecting target user's search shopping type Under, extract the web-based history behavior record of the shopping type of the whole network user；Shopping type again based on the whole network user is gone through History network behavior records, and determines the recommendation information of shopping type corresponding with the target user；Finally by the shopping type Recommendation information be illustrated in result of page searching corresponding with the search content that the target user searches for.In this way, logical in user It crosses in the case of search engine initiation shopping class search, it can be by the web-based history behavior record of the shopping type of the whole network user, in advance It surveys user potentially to do shopping the search need of class, further determines that out the recommendation information of the relevant shopping type of user, carrying out It, can be by the recommendation information of the relevant shopping type of user together with displaying when search result is shown.In this way, by initiating to purchase in user The search need of preposition user's shopping class, the search efficiency and user's body of significant increase search engine when the search of species type It tests, personalized search recommendation results is provided, increase the realization efficiency and user's viscosity of search engine.

Description of the drawings

By reading the detailed description of hereafter preferred embodiment, various other advantages and benefit are common for this field Technical staff will become clear.Attached drawing only for the purpose of illustrating preferred embodiments, and is not considered as to the present invention Limitation.And throughout the drawings, the same reference numbers will be used to refer to the same parts.In the accompanying drawings：

Fig. 1 is a kind of flow chart of shopping information method for pushing in first embodiment of the invention；

Fig. 2 is a kind of flow chart of shopping information method for pushing in second embodiment of the invention；

Fig. 3 is a kind of schematic diagram of shopping information pusher in third embodiment of the invention；

Fig. 4 is a kind of schematic diagram of shopping information pusher in fourth embodiment of the invention；

Fig. 5 is the schematic diagram of the electronic equipment in fifth embodiment of the invention.

Specific implementation mode

The present embodiment discloses a kind of shopping information method for pushing, device and electronic equipment, by initiating shopping class in user The search need of preposition user's shopping class when the search of type, the search efficiency and user experience of significant increase search engine carry For personalized search recommendation results, increase the realization efficiency and user's viscosity of search engine.This method includes：Detecting mesh It marks user to search in the case of the search content of shopping type, extracts the web-based history behavior record of the shopping type of the whole network user； The web-based history behavior record of shopping type based on the whole network user determines shopping type corresponding with the target user Recommendation information；The recommendation information of the shopping type is illustrated in search knot corresponding with the shopping search content of type In the fruit page.

Technical solution of the present invention is described in detail below by attached drawing and specific embodiment, it should be understood that the application Specific features in embodiment and embodiment are the detailed description to technical scheme, rather than to present techniques The restriction of scheme, in the absence of conflict, the technical characteristic in the embodiment of the present application and embodiment can be combined with each other.

The terms "and/or", only a kind of incidence relation of description affiliated partner, indicates that there may be three kinds of passes System, for example, A and/or B, can indicate：Individualism A exists simultaneously A and B, these three situations of individualism B.In addition, herein Middle character "/", it is a kind of relationship of "or" to typically represent forward-backward correlation object.

Embodiment

Referring to FIG. 1, first embodiment of the invention provides a kind of shopping information method for pushing, the shopping information method for pushing Include the following steps：

S101：In the search content for detecting target user's search shopping type, the shopping of the whole network user is extracted The web-based history behavior record of type；

S102：The web-based history behavior record of shopping type based on the whole network user determines and the target user The recommendation information of corresponding shopping type；

S103：The recommendation information of the shopping type is illustrated in search corresponding with the shopping search content of type In results page.

Specifically, in the present embodiment, shopping information method for pushing is mainly used in the server end of search engine, when So, client can also be applied to.User when client inputs the search content of shopping type by search engine, draw by search It holds up the server of the search content transmission of the shopping type to search engine, when server receives the search of the shopping type After content, corresponding search result is retrieved.On this basis, server can also obtain the history of the shopping type of the whole network user Network behavior is noted down, and prediction user potentially does shopping the search need of class, further determines that out the relevant shopping type of user Recommendation information can be by the recommendation information of the relevant shopping type of user together with displaying when scanning for result displaying.In this way, The search need for class of being done shopping by preposition user when initiating the search of shopping type in user, the inquiry of significant increase search engine Efficiency and user experience provide personalized search recommendation results, increase the realization efficiency and user's viscosity of search engine.

Further, in the present embodiment, the search content of above-mentioned steps S101, the shopping type include shopping network station name Claim, any one or more in shopping website link and trade name combines.

Specifically, in the present embodiment, initiating the search content of search shopping type in target user, triggering is held Shopping information method for pushing in row the present embodiment, such as：Target user is searching for the title of site search electric business website A, electricity In the case of the network address of quotient B or the title of commodity A, the shopping information method for pushing executed in the present embodiment can be triggered, is user Push the recommendation information of personalized shopping type.In specific implementation process, the search content for type of doing shopping includes shopping network Station name shopping website is linked to be combined with any one or more in trade name, it is, of course, also possible to be other content, here, The application does not limit.

Method in the present embodiment can just be triggered in the search content for initiating to search for shopping type, can be effective Avoid related push carried out to non-shopping type search, cause the interference to user, can further reduce equipment Data transmission is born, and the Experience Degree of user is improved.

Further, after the shopping information method for pushing in the present embodiment is triggered, step S101 is in specific implementation process In, it can be achieved by the steps of：

Specifically, in the present embodiment, need to obtain preset time range (such as：1 hour, 5 hours, 24 hours etc.) in The whole network user shopping type search record, shopping type click record and shopping type browsing record in it is any one Kind or multiple combinations.Such as：The search record for type of doing shopping can be that the whole network user searches for shopping network in preset time range The record that any one or more in station name, shopping website link and trade name combines.Such as：In user A when away from current Before carving 20 minutes in the case of the title of search site search electric business website A, determine that this is recorded as the shopping type of the whole network user Search record.

For another example：Shopping type click record can be the whole network user click in preset time range shopping website, Shopping website links the record combined with any one or more in shopping items link.Such as：In user B away from current time 30 In the case of clicking electric business website B before minute, determine that this is recorded as the click of the shopping type of the whole network user record.

For another example：The browsing record of shopping type can be the shopping website that the whole network user browses in preset time range And/or the record of shopping items link.Such as：The commodity A feelings of electric business website B are browsed before away from 30 minutes current times in user C Under condition, determine that this is recorded as the browsing of the shopping type of the whole network user record, in the browsing of the shopping type of record the whole network user When record, in order to ensure the validity of record, it is also contemplated that browsing duration is more than preset duration (such as by browsing duration：1 Minute, 5 minutes etc.) commodity browsing be denoted as the whole network user shopping type browsing record.

In this way, the web-based history behavior record of the shopping type of the whole network user can effectively be counted.

Further, it after the web-based history behavior record for the shopping type for getting the whole network user, executes in the present embodiment When step S102, it can be achieved by the steps of：

Specifically, in the present embodiment, collaborative filtering model may be used to filter out corresponding shopping class in step S102 The recommendation information of type, it is, of course, also possible to be realized using other modes, here, the application is not limited.In step s 102, first First, the web-based history behavior record of the shopping type of the whole network user based on acquisition is needed, determines candidate items, waited determining When option, it can be achieved by the steps of：

Specifically, since the web-based history behavior record of the whole network user includes the whole network user in preset time range The browsing record etc. of the search record for type of doing shopping, the click record of shopping type, shopping type.So determining candidate item When mesh, searching times can be filtered out from the search of the shopping type of the whole network user in preset time range record and be more than The search content of first preset times is candidate items.Such as：It is pre- to be more than first for the searching times of the whole network user in 24 hours If number is (such as：1000 times, it is 5000 inferior) the search content of shopping type include commodity A, shopping website B, commodity B etc., then Commodity A, shopping website B, commodity B can screen as candidate items.

It similarly, can be from the point of the shopping type of the whole network user in preset time range when determining candidate items It is candidate items to hit in record and filter out number of clicks more than the click on content of the second preset times.Such as：It is complete in 24 hours The number of clicks of network users is more than the second preset times (such as：1000 times, it is 5000 inferior) the click on content of shopping type include Commodity C, shopping website A, commodity D etc., then commodity C, shopping website A, commodity D can also screen as candidate items.

It similarly, can be from the clear of the shopping type of the whole network user in preset time range when determining candidate items It is candidate items to look at and filter out number of visits in recording more than the browsing content of third preset times.Such as：It is complete in 24 hours The number of visits of network users is more than third preset times (such as：1000 times, it is 5000 inferior) the browsing content of shopping type include Commodity E, shopping website C, commodity F etc., then commodity E, shopping website C, commodity F can also screen as candidate items.In this way The candidate items that mode is determined more meet the actual shopping intention change trend of the whole network user, and then are determined according to candidate items The recommendation information of the shopping type gone out more meets user demand.

In conjunction with above-mentioned three kinds of situations, the whole network user in preset time range can also be considered, a certain content is searched The number summation of rope, click and browsing is more than predetermined threshold value in the number summation, also can be using the content as candidate Project.

In specific implementation process, determine that the mode of candidate items is not limited to aforesaid way, it can also be according to practical need It is set, such as：Only consider target user shopping class web-based history behavior record, determine target user search for, It clicks and the more content of number of visits is as candidate items, here, the application is not limited.

Determining candidate items, you can establish user's rating matrix that the whole network user is directed to candidate items, use Family rating matrix can indicate as follows：

In above formula, U_iIndicate the user i, I in the whole network user_jIt is that user i comments candidate items j for candidate items j, Rij Point.In the present embodiment, user can indicate the scorings of candidate items with Binary Zero and 1, and 0 indicates user to candidate item Mesh is lost interest in, and 1 indicates that user is interested in candidate items.Scoring of the user to candidate items is being determined in this way When, the web-based history behavior record for the shopping type for calling the user is needed, such as：Search record, when the user searches for the candidate The number of project is more than preset search number, determines that the user is 1 to the scoring of the candidate items.Conversely, when the user searches for The number of the candidate items is less than or equal to preset search number, determines that the user is 0 to the scoring of the candidate items.

Alternatively, the number that the user searches for all candidate items can also be obtained, when the user searches for the candidate items The percentage that number accounts for the number that the user searches for all candidate items is more than preset percentage, determines the user to the candidate item Purpose scoring is 1.Conversely, when the number that the user searches for the candidate items accounts for the number that the user searches for all candidate items Percentage is less than or equal to preset percentage, determines that the user is 0 to the scoring of the candidate items.

It is, of course, also possible to which the number that user is directly searched for certain candidate items accounts for time that the user searches for all candidate items Several percentage is as the user to the score value of the candidate items.In specific implementation process, other modes can also be used Scoring of the user to candidate items is determined, here, the application is not limited.

Further, after establishing user's rating matrix, the method in the present embodiment can be determined according to rating matrix Neighbor user collection similar with target user.It, can be as follows when determining the corresponding neighbor user collection of target user It realizes：

Based on the rating matrix, the similitude of the target user and other users in the whole network user are calculated；Base The similitude of other users in the target user and the whole network user determines that neighbours similar with the target user use Family collection.

Specifically, in the present embodiment, it can be based on the rating matrix of above-mentioned foundation, using Euclidean distance formula meter Calculate target user and the whole network other users Euclidean distance, the Euclidean distance can be used to indicate that the target user and The similitude of other users.Euclidean distance formula isFormula surface user X and user y's Euclidean distance, Rxj are scorings of the user x to candidate items j, and Ryj is scorings of the user y to candidate items j.It is used with target The Euclidean distance at family is bigger, shows that the similitude of the user and target user are higher, the shopping of the user and target user Hobby it is more similar.Certainly, in the present embodiment, can also using cosine similarity formula come calculate target user with it is complete The similitude of net other users, cosine similarity formula areWherein, V_xIt is user x to all candidate items Scoring vector, V_yIt is user y vectorial to the scoring of all candidate items.It is bigger with the cosine similarity of target user, show The user is more similar to the hobby of the shopping of target user.In specific implementation process, target user and other use are determined The mode of the similitude at family can be set according to actual needs, here, the application is not limited.

Further, after determining similitude of the target user with the whole network other users, it may be used but be not limited to following Two ways determines neighbor user collection similar with target user：

First way：Determine similar with target user neighbor user collection include in the whole network user with it is described The similitude of target user is more than the user of the first predetermined threshold value.

Specifically, in the present embodiment, the first predetermined threshold value can be preset, when in the whole network user with target user's When similitude is more than first predetermined threshold value, neighbor user similar with target user can be added into and concentrated, i.e., from the whole network User filters out user of the similarity more than the first predetermined threshold value as neighbor user collection similar with target user.

The second way：Determine similar with target user neighbor user collection include in the whole network user with it is described The similitude of target user arrange from large to small after preceding first preset number user.

Specifically, in the present embodiment, after determining similitude of the target user with the whole network other users, can incite somebody to action It is ranked up from large to small by similitude, then, will come the user of the first preset number of front as with target user Similar neighbor user collection.Such as：The whole network user after being ranked up from large to small by the similitude with target user includes using Family 1, user 3, user 4, user 5, user 2 are determined as neighbor user similar with target user when first preset number is 2 Collection includes user 1, user 3.

In specific implementation process, first in the first predetermined threshold value and the second way in above-mentioned first way Preset number can be set according to actual needs, here, the application is not limited.It is, of course, also possible to using other modes Neighbor user collection is determined, here, the application is not limited.

Further, after determining neighbor user collection, the recommendation to target user can be generated according to the shopping preferences of neighbours Project.Specifically, determining that recommended project can be realized by the following two kinds mode according to neighbor user collection：

First way：Based on the neighbor user collection, determine the target user to each item in the candidate items Purpose interest-degree predicted value；Determine that the project that interest-degree predicted value is more than the second predetermined threshold value in the candidate items is recommendation items The project of preceding second preset number after interest-degree predicted value arranges from large to small in mesh or the determining candidate items is to recommend Project.

Specifically, in the present embodiment, neighbor user collection can be based on, determine target user to each item in candidate items Formula may be used when calculating interest-degree predicted value of the target user to candidate items in purpose interest-degree predicted valueWherein,It is average scores of the target user u to all candidate items, i is neighbor user collection User, c_iIt is the similarity between target family u and neighbor user i, r_ijIt is scorings of the neighbor user i to candidate items j,It is adjacent Occupy average scores of the user i to all candidate items.

In this way, the second predetermined threshold value can be preset, by that can determine target user to institute by above-mentioned formula There is the interest-degree predicted value of candidate items, and then filters out interest-degree predicted value of the target user to it from all candidate items Project more than the second predetermined threshold value is recommended project.

Alternatively, after determining target user to the interest-degree predicted value of each candidate items, candidate items can be pressed Interest-degree predicted value is ranked up from large to small, then, will come the candidate items of the second preset number of front as recommendation Project.Such as：Candidate items after being ranked up from large to small by interest-degree predicted value include project 1, project 3, project 4, item Mesh 5, project 2 determine that recommended project includes project 1, project 3, project 4 when second preset number is 3.

The second way：Determine all neighbor users of the neighbor user concentration to each project in the candidate items Weighted average interest-degree；Determine that the project that weighted average interest-degree is more than third predetermined threshold value in the candidate items is to recommend Project determines that the project of the preceding third preset number after weighted average interest-degree arranges from large to small in the candidate items is Recommended project.

Specifically, in the present embodiment, each candidate items can be directed to, determine that all neighbours that neighbor user is concentrated use To the weighted average interest-degree of the candidate items, weighting coefficient can be set according to actual needs at family, here, the application is not It is limited.In turn, third predetermined threshold value can be preset, since all neighbor users can be determined to each candidate items Weighted average interest-degree, and then filter out from all candidate items the item that weighted average interest-degree is more than third predetermined threshold value Mesh is recommended project.

Alternatively, after determining the weighted average interest-degree of each candidate items, candidate items can be pressed weighted average Interest-degree is ranked up from large to small, then, will come the candidate items of the third preset number of front as recommended project.Than Such as：Candidate items after being ranked up from large to small by weighted average interest-degree include project 1, project 3, project 4, project 5, item Mesh 2 determines that recommended project includes project 1, project 3, project 4 when third preset number is 3.

After determining recommended project, it is also necessary to determine pushing away for shopping type corresponding with target user based on recommended project Recommend information.Specifically, the recommendation information of the shopping type includes candidate search word corresponding with the recommended project and/or net Page link.

Specifically, in the present embodiment, the recommended project determined may be the search term or shopping class of some shopping classes Website, so, the recommendation information for recommending the shopping type of target user include candidate search word corresponding with recommended project and/ Or web page interlinkage.Such as：Recommended project includes the title of electric business website A, the title of commodity B, recommends the shopping of target user The recommendation information of type is the corresponding candidate search word of title of the network address and commodity B of electric business website A, or is electric business website The purchase link etc. of the corresponding candidate search word of title and commodity B of A, target user can click directly on candidate search word, And then obtain the search result of the candidate search word.Target user can click directly on the web page interlinkage of recommendation, into the webpage Link corresponding website.In specific implementation process, the recommendation information determined according to recommended project can carry out according to actual needs Setting, here, the application is not limited.

Further, in the present embodiment, the recommendation information of the shopping type, which specifically includes user, can directly place an order purchase Merchandise items, the method further includes：User is responded to the trigger action of the merchandise items, loads the merchandise items pair The purchase webpage answered buys the merchandise items for the user by the purchase webpage.

Specifically, in the present embodiment, the recommended project determined is also possible to be some merchandise items, so, it recommends The recommendation information of the shopping type of target user includes the purchase webpage of merchandise items corresponding with recommended project.Such as：Commodity B Purchase link etc., target user can go to its by clicking directly on the merchandise items of recommendation and buy web page interlinkage, Jin Erke The commodity of quick purchase intention.

Further, in step s 103, the recommendation information by the shopping type is needed to be illustrated in and the shopping type The corresponding result of page searching of search content in.In the recommendation information of displaying shopping type, shopping class can be illustrated in Below the corresponding search result of the search content of type, further, the recommendation information of the shopping class determined in the present embodiment can be with It is illustrated in the lower section of the first item result in search result.Such as：Target user initiates the search of search electric business website A titles When, search result includes the official website network address and other continuous item search results of electric business website A, through this embodiment in side The recommendation information for the shopping type that method is determined can be illustrated in the lower section of the official website network address item of electric business website A, be convenient for user It checks.

Further, in the present embodiment, it is illustrated in and the shopping type by the recommendation information of the shopping type The corresponding result of page searching of content is searched for, can also be achieved by the steps of：

Searching for the shopping type searched for the target user is determined from the recommendation information of the shopping type The relevant recommendation information of rope content；By the relevant recommendation of search content for the shopping type searched for the target user Breath is illustrated in result of page searching corresponding with the shopping search content of type.

Specifically, in the present embodiment, in order to enable the shopping category information of push is more accorded with closer to the buying intention of user The shopping need for sharing family can be from the recommendation information determined based on recommended project in the recommendation information of displaying shopping type In determine that the relevant recommendation information of search content searched for target user pushes.Such as：Target user initiates electric business After the search of website A, the recommendation information packet for the shopping type that the web-based history behavior of the shopping class based on the whole network user is determined When including electric business website B, commodity A, commodity B and commodity C, if electric business website A is to sell the shopping website of books, and electric business net The B that stands is the shopping website for selling dress ornament, and commodity A is the commodity of dress ornament class, and commodity B and commodity C are books class commodity, then may be used Commodity B and the corresponding recommendation informations of commodity C are illustrated in the page of search result, specifically, electric business net can be illustrated in Stand A official website search result lower section, prediction user may books commodity interested.

For another example：After target user initiates the search of commodity D, determined based on the web-based history behavior of the shopping class of the whole network user When the recommendation information of the shopping type gone out includes electric business website B, commodity A, commodity B and commodity C, if commodity D is mother and baby quotient Product, electric business website B are the shopping website for selling dress ornament, and commodity A is the commodity of dress ornament class, and commodity B and commodity C are mother and baby's class Commodity B and the corresponding recommendation informations of commodity C can be then illustrated in the page of search result, specifically, can show by commodity In the lower section of the official website search result of electric business website A, prediction user may books commodity interested.In this way, can will be with target User searches for the relevant recommendation information of content and is pushed to target user so that target user can be by the information of recommendation rapidly Interested commodity are navigated to, user experience is promoted.

Further, the method in the present embodiment can also will search for the higher recommendation of the content degree of correlation with target user Breath is illustrated in front, will search for the lower recommendation information of the content degree of correlation with target user and be illustrated in below, such as：Target user After the search for initiating commodity D, the recommendation for the shopping type that the web-based history behavior of the shopping class based on the whole network user is determined When breath includes electric business website B, commodity A, commodity B and commodity C, if commodity D is mother and baby's commodity, electric business website B is that sale takes The shopping website of decorations, commodity A are the commodity of dress ornament class, and commodity B and commodity C are mother and baby's class commodity, in displaying recommendation information When, the corresponding recommendation informations of commodity B and commodity C can be shown to forefront, rear shows electric business website B, commodity A, commodity B. It is used to target in this way, the higher recommendation information of the content degree of correlation will be searched for target user and be illustrated in most eye-catching location push Family, the target user enable quickly locate interested commodity by the information of recommendation, promote user experience.

Shopping information method for pushing in the present embodiment, can initiate that electric business website, commodity etc. are relevant to be looked into target user After inquiry, the shopping need of preposition user predicts the next interested commodity of user and buying intention, can significant increase The search efficiency and user experience of search engine.

Fig. 2 is referred to, the second embodiment of the present invention provides a kind of shopping information method for pushing, including：

S201：In the search content for detecting target user's search shopping type, the shopping of the whole network user is extracted The web-based history behavior record of type；

S202：The web-based history behavior record of shopping type based on the whole network user determines and the target user Similar similar users collection；

S203：The information of the interested shopping type of each similar users, determining and institute are concentrated based on the similar users State the recommendation information of the corresponding shopping type of target user；

S204：The recommendation information of the shopping type is illustrated in search corresponding with the shopping search content of type In results page.

Specifically, in the present embodiment, shopping information method for pushing is mainly used in the server end of search engine, when So, client can also be applied to.User when client inputs the search content of shopping type by search engine, draw by search It holds up the server of the search content transmission of the shopping type to search engine, when server receives the search of the shopping type After content, corresponding search result is retrieved.On this basis, server can also obtain the history of the shopping type of the whole network user Network behavior is noted down, and determines similar users collection similar with target user, the similar users concentrated further according to similar users The web-based history behavior record for class of doing shopping, prediction user potentially do shopping the search need of class, further determine that out user's correlation Shopping type recommendation information, scan for result displaying when, can by user it is relevant shopping type recommendation information connect With displaying.In this way, the search need for class of being done shopping by preposition user when initiating the search of shopping type in user, significant increase are searched The search efficiency and user experience held up are indexed, personalized search recommendation results are provided, the realization efficiency of search engine is increased With user's viscosity.

Further, in the present embodiment, the search content of above-mentioned steps S201, the shopping type include shopping network station name Claim, any one or more in shopping website link and trade name combines.

Further, after the shopping information method for pushing in the present embodiment is triggered, step S201 is in specific implementation process In, it can be achieved by the steps of：

Further, it after the web-based history behavior record for the shopping type for getting the whole network user, executes in the present embodiment Step S202 needs the web-based history behavior record of the shopping type based on the whole network user, determines phase similar with target user Collect like user.

Specifically, in the present embodiment, the historical search with target user in the whole network user, history can be clicked and/ Or the similar user of content of historical viewings is as similar users.Such as：The historical search of the shopping type of target user, history Click and/or historical impressions are most three be A commodity, B commodity, C commodity, D commodity.If the whole network user's history is searched Rope, history are clicked and/or what historical impressions were most includes arbitrary three in A commodity, B commodity, C commodity, D commodity, you can Determine that the user is similar users and can form similar users collection in this way.Again alternatively, before can also using It states the method referred in first embodiment and determines similar users collection, specifically repeat no more, referring to previous embodiment.

In turn, after determining similar users collection, step S203 is executed, each similar users are concentrated based on similar users The information of interested shopping type determines the recommendation information of shopping type corresponding with the target user.

Specifically, in the present embodiment, each interested shopping type of similar users can be concentrated according to similar users Information, determine the information of the shopping type of common interest, the information of the shopping type of common interest be pushed to mesh Mark user.Such as：Similar users collection includes user 1, user 2, user 3 and user 4, the letter of the interested shopping type of user 1 Breath includes A shopping websites, B commodity and C commodity, the interested information for doing shopping type of user 2 include A shopping websites, B commodity and The information of D commodity, the interested shopping type of user 3 includes A shopping websites, B commodity and E commodity, 4 interested shopping of user The information of type includes B shopping websites, C commodity and E commodity, when there is predetermined number similar users interested in same information, Determine that the information is to recommend the information of target user.When predetermined number is set as 2, then A shopping websites, B commodity, C commodity Information corresponding with E commodity is the recommendation information of shopping type.

Certainly, in specific implementation process, determine that the recommendation information of similar users collection and type of doing shopping can be according to reality It needs to be configured, here, the application is not limited.

It, can be by the recommendation information of the shopping type and search result together with exhibition after the recommendation information for determining shopping type Show, the mode of displaying can refer to the mode in first embodiment, here, the application does not repeat.

Fig. 3 is please referred to, third embodiment of the invention additionally provides a kind of shopping information pusher, including：

Acquiring unit 301, in the search content for detecting target user's search shopping type, extracting the whole network The web-based history behavior record of the shopping type of user；

Determination unit 302 is used for the web-based history behavior record of the shopping type based on the whole network user, determining and institute State the recommendation information of the corresponding shopping type of target user；

Display unit 303, for by it is described shopping type recommendation information be illustrated in it is described shopping type search in Hold in corresponding result of page searching.

Specifically, in the present embodiment, shopping information pusher can be arranged in the server, can also be arranged and move Dynamic terminal device, such as mobile phone, tablet computer, laptop equipment, can also be the equipment such as desktop computer, certainly can be with It is other electronic equipments, here, the application is not limited.The mode that shopping information pusher carries out shopping information push exists It is described in detail in aforementioned first embodiment, here, this embodiment is not repeated.

As a kind of optional embodiment, the determination unit 302 includes：

As a kind of optional embodiment, the acquiring unit 301 is used for：

As a kind of optional embodiment, first determining module is used for：

As a kind of optional embodiment, the third determining module is used for：

As a kind of optional embodiment, the 4th determining module is used for：

As a kind of optional embodiment, the display unit is used for：

As a kind of optional embodiment, the search content of the shopping type includes：Shopping website title, shopping website Any one or more in link and trade name combines.

As a kind of optional embodiment, the display unit is used for：

As a kind of optional embodiment, the recommendation information of the shopping type, which specifically includes user, can directly place an order purchase Merchandise items, described device further includes：

Fig. 4 is please referred to, third embodiment of the invention additionally provides a kind of shopping information pusher, including：

Acquiring unit 401 is used to, in the search content for detecting target user's search shopping type, extract the whole network The web-based history behavior record of the shopping type of user；

First determination unit 402 is used for the web-based history behavior record of the shopping type based on the whole network user, determines Similar users collection similar with the target user；

Second determination unit 402, for concentrating each interested shopping type of similar users based on the similar users Information, determine it is corresponding with the target user do shopping type recommendation information；

Display unit 403, for by it is described shopping type recommendation information be illustrated in it is described shopping type search in Hold in corresponding result of page searching.

Specifically, in the present embodiment, shopping information pusher can be arranged in the server, can also be arranged and move Dynamic terminal device, such as mobile phone, tablet computer, laptop equipment, can also be the equipment such as desktop computer, certainly can be with It is other electronic equipments, here, the application is not limited.The mode that shopping information pusher carries out shopping information push exists It is described in detail in aforementioned second embodiment, here, this embodiment is not repeated.

Fifth embodiment of the invention additionally provides a kind of electronic equipment, for convenience of description, illustrates only and present invention reality The relevant part of example is applied, particular technique details does not disclose, please refers to present invention method part.The electronic equipment can be with Can also be that (Personal Digital Assistant, individual digital help including mobile phone, tablet computer, PDA for server Reason), POS (Point of Sales, point-of-sale terminal), the arbitrary electronic equipment such as vehicle-mounted computer, by taking electronic equipment is mobile phone as an example：

Fig. 5 shows the block diagram with the part-structure of the relevant mobile phone of electronic equipment provided in an embodiment of the present invention.Ginseng Fig. 5 is examined, mobile phone includes：Radio frequency (Radio Frequency, RF) circuit 510, memory 520, input unit 530, display unit 540, sensor 550, voicefrequency circuit 560, Wireless Fidelity (wireless-fidelity, Wi-Fi) module 570, processor 580, And the equal components of power supply 590.It will be understood by those skilled in the art that handset structure shown in Fig. 5 is not constituted to mobile phone It limits, may include either combining certain components or different components arrangement than illustrating more or fewer components.

Each component parts of mobile phone is specifically introduced with reference to Fig. 5：

RF circuits 510 can be used for receiving and sending messages or communication process in, signal sends and receivees, particularly, by base station After downlink information receives, handled to processor 580；In addition, the data for designing uplink are sent to base station.In general, RF circuits 510 Including but not limited to antenna, at least one amplifier, transceiver, coupler, low-noise amplifier (Low Noise Amplifier, LNA), duplexer etc..In addition, RF circuits 510 can also be communicated with network and other equipment by radio communication. Above-mentioned wireless communication can use any communication standard or agreement, including but not limited to global system for mobile communications (Global System of Mobile communication, GSM), general packet radio service (General Packet Radio Service, GPRS), CDMA (Code Division Multiple Access, CDMA), wideband code division multiple access (Wideband Code Division Multiple Access, WCDMA), long term evolution (Long Term Evolution, LTE), Email, short message service (Short Messaging Service, SMS) etc..

Memory 520 can be used for storing software program and module, and processor 580 is stored in memory 520 by operation Software program and module, to execute various function application and the data processing of mobile phone.Memory 520 can include mainly Storing program area and storage data field, wherein storing program area can storage program area, the application journey needed at least one function Sequence (such as sound-playing function, image player function etc.) etc.；Storage data field can be stored to be created according to using for mobile phone Data (such as audio data, phone directory etc.) etc..It, can be in addition, memory 520 may include high-speed random access memory Including nonvolatile memory, for example, at least a disk memory, flush memory device or other volatile solid-states Part.

Input unit 530 can be used for receiving the number or character information of input, and generate with the user setting of mobile phone with And the related key signals input of function control.Specifically, input unit 530 may include that touch panel 531 and other inputs are set Standby 532.Touch panel 531, also referred to as touch screen, collect user on it or neighbouring touch operation (such as user use The operation of any suitable object or attachment such as finger, stylus on touch panel 531 or near touch panel 531), and root Corresponding attachment device is driven according to preset formula.Optionally, touch panel 531 may include touch detecting apparatus and touch Two parts of controller.Wherein, the touch orientation of touch detecting apparatus detection user, and the signal that touch operation is brought is detected, Transmit a signal to touch controller；Touch controller receives touch information from touch detecting apparatus, and is converted into touching Point coordinates, then give processor 580, and order that processor 580 is sent can be received and executed.Furthermore, it is possible to using electricity The multiple types such as resistive, condenser type, infrared ray and surface acoustic wave realize touch panel 531.In addition to touch panel 531, input Unit 530 can also include other input equipments 532.Specifically, other input equipments 532 can include but is not limited to secondary or physical bond It is one or more in disk, function key (such as volume control button, switch key etc.), trace ball, mouse, operating lever etc..

Display unit 540 can be used for showing information input by user or be supplied to user information and mobile phone it is various Menu.Display unit 540 may include display panel 541, optionally, liquid crystal display (Liquid Crystal may be used Display, LCD), the forms such as Organic Light Emitting Diode (Organic Light-Emitting Diode, OLED) it is aobvious to configure Show panel 541.Further, touch panel 531 can cover display panel 541, when touch panel 531 detect it is on it or attached After close touch operation, processor 580 is sent to determine the type of touch event, is followed by subsequent processing device 580 according to touch event Type corresponding visual output is provided on display panel 541.Although in Figure 5, touch panel 531 and display panel 541 It is that input and the input function of mobile phone are realized as two independent components, but in some embodiments it is possible to by touch-control Panel 531 and display panel 541 are integrated and that realizes mobile phone output and input function.

Mobile phone may also include at least one sensor 550, such as optical sensor, motion sensor and other sensors. Specifically, optical sensor may include ambient light sensor and proximity sensor, wherein ambient light sensor can be according to ambient light Light and shade adjust the brightness of display panel 541, proximity sensor can close display panel 541 when mobile phone is moved in one's ear And/or backlight.As a kind of motion sensor, accelerometer sensor can detect in all directions (generally three axis) acceleration Size, size and the direction of gravity are can detect that when static, can be used to identify the application of mobile phone posture, (for example horizontal/vertical screen is cut Change, dependent game, magnetometer pose calibrating), Vibration identification correlation function (such as pedometer, tap) etc.；May be used also as mobile phone The other sensors such as gyroscope, barometer, hygrometer, thermometer, the infrared sensor of configuration, details are not described herein.

Voicefrequency circuit 560, loud speaker 561, microphone 562 can provide the audio interface between user and mobile phone.Audio-frequency electric The transformed electric signal of the audio data received can be transferred to loud speaker 561 by road 560, and sound is converted to by loud speaker 561 Signal exports；On the other hand, the voice signal of collection is converted to electric signal by microphone 562, is turned after being received by voicefrequency circuit 560 It is changed to audio data, then by after the processing of audio data output processor 580, through RF circuits 510 to be sent to such as another mobile phone, Or audio data is exported to memory 520 to be further processed.

WiFi belongs to short range wireless transmission technology, and mobile phone can help user's transceiver electronics postal by WiFi module 570 Part, browsing webpage and access streaming video etc., it has provided wireless broadband internet to the user and has accessed.Although Fig. 5 is shown WiFi module 570, but it is understood that, and it is not belonging to must be configured into for mobile phone, it can not change as needed completely Become in the range of the essence of invention and omits.

Processor 580 is the control centre of mobile phone, using the various pieces of various interfaces and connection whole mobile phone, is led to It crosses operation or executes the software program and/or module being stored in memory 520, and call and be stored in memory 520 Data execute the various functions and processing data of mobile phone, to carry out integral monitoring to mobile phone.Optionally, processor 580 can wrap Include one or more processing units；Preferably, processor 580 can integrate application processor and modem processor, wherein answer With the main processing operation system of processor, user interface and application program etc., modem processor mainly handles wireless communication. It is understood that above-mentioned modem processor can not also be integrated into processor 580.

Mobile phone further includes the power supply 590 (such as battery) powered to all parts, it is preferred that power supply can pass through power supply pipe Reason system and processor 580 are logically contiguous, to realize management charging, electric discharge and power managed by power-supply management system Etc. functions.

Although being not shown, mobile phone can also include camera, bluetooth module etc., and details are not described herein.

In embodiments of the present invention, the processor 580 is also with the following functions：

In embodiments of the present invention, the search content of the shopping type includes：Shopping website title, shopping website link It is combined with any one or more in trade name.

In embodiments of the present invention, the recommendation information of the shopping type specifically includes user and can directly place an order the quotient of purchase Product object, the processor 580 are also with the following functions：

Sixth embodiment of the invention provides a kind of computer readable storage medium, is stored thereon with computer program, this If inventing the integrated functional unit of the shopping information pusher in the third and fourth embodiment with SFU software functional unit Form realize and when sold or used as an independent product, can be stored in a computer read/write memory medium. Based on this understanding, the present invention realizes all or part in the shopping information method for pushing of above-mentioned the first and second embodiments Flow can also instruct relevant hardware to complete by computer program, and the computer program can be stored in a meter In calculation machine readable storage medium storing program for executing, the computer program is when being executed by processor, it can be achieved that the step of above-mentioned each embodiment of the method Suddenly.Wherein, the computer program includes computer program code, the computer program code can be source code form, Object identification code form, executable file or certain intermediate forms etc..The computer-readable medium may include：Institute can be carried State computer program code any entity or device, medium, USB flash disk, mobile hard disk, magnetic disc, CD, computer storage, only Memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electricity is read to carry Wave signal, telecommunication signal and software distribution medium etc..It should be noted that the content that the computer-readable medium includes can To carry out increase and decrease appropriate according to legislation in jurisdiction and the requirement of patent practice, such as in certain jurisdictions, root According to legislation and patent practice, computer-readable medium does not include electric carrier signal and telecommunication signal.

Although preferred embodiments of the present invention have been described, it is created once a person skilled in the art knows basic Property concept, then additional changes and modifications may be made to these embodiments.So it includes excellent that the following claims are intended to be interpreted as It selects embodiment and falls into all change and modification of the scope of the invention.

Obviously, various changes and modifications can be made to the invention without departing from essence of the invention by those skilled in the art God and range.In this way, if these modifications and changes of the present invention belongs to the range of the claims in the present invention and its equivalent technologies Within, then the present invention is also intended to include these modifications and variations.

Claims

1. a kind of shopping information method for pushing, which is characterized in that including：

In the search content for detecting target user's search shopping type, the history of the shopping type of the whole network user is extracted Network behavior records；

The web-based history behavior record of shopping type based on the whole network user determines shopping corresponding with the target user The recommendation information of type；

The recommendation information of the shopping type is illustrated in result of page searching corresponding with the shopping search content of type In.

2. the method as described in claim 1, which is characterized in that the history net of the shopping type based on the whole network user Network behavior record determines the recommendation information of shopping type corresponding with the target user, including：

Determine that recommendation information corresponding with the recommended project is the recommendation information of type of doing shopping corresponding with the target user.

3. method as claimed in claim 1 or 2, which is characterized in that the web-based history behavior record for obtaining the whole network user, Including：

Obtain the search record of the shopping type of the whole network user in preset time range, the click record of shopping type and purchase Any one or more in the browsing record of species type combines.

4. method as described in any one of claims 1-3, which is characterized in that the shopping type based on the whole network user Web-based history behavior record determines candidate items, including：

Determine that searching times are more than first in the search record of the shopping type of the whole network user in the preset time range The search content of preset times is candidate items；And/or

Determine that the click record midpoint machine number of the shopping type of the whole network user in the preset time range is more than second The click on content of preset times is candidate items；And/or

Determine that number of visits is more than third in the browsing record of the shopping type of the whole network user in the preset time range The browsing content of preset times is candidate items.

5. the method as described in claim 1-4 is any, which is characterized in that it is described to be based on the rating matrix, it determines described complete Neighbor user collection similar with the target user in network users, including：

Based on the similitude of other users in the target user and the whole network user, determination is similar with the target user Neighbor user collection.

6. a kind of shopping information method for pushing, which is characterized in that including：

The web-based history behavior record of shopping type based on the whole network user, determination are similar similar to the target user User collects；

The information that the interested shopping type of each similar users is concentrated based on the similar users, is determined and the target user The recommendation information of corresponding shopping type；

7. a kind of shopping information pusher, which is characterized in that including：

Acquiring unit, in the search content for detecting target user's search shopping type, extracting the whole network user's The web-based history behavior record for type of doing shopping；

Determination unit is used for the web-based history behavior record of the shopping type based on the whole network user, determines and the target The recommendation information of the corresponding shopping type of user；

Display unit, it is corresponding with the shopping search content of type for being illustrated in the recommendation information of the shopping type In result of page searching.

8. a kind of shopping information pusher, which is characterized in that including：

First determination unit, be used for the shopping type based on the whole network user web-based history behavior record, determination with it is described The similar similar users collection of target user；

Second determination unit, the information for concentrating the interested shopping type of each similar users based on the similar users, Determine the recommendation information of shopping type corresponding with the target user；

9. a kind of electronic equipment, which is characterized in that including processor and memory：

The memory is used to store the program that perform claim requires any one of 1 to 6 the method；

The processor is configurable for executing the program stored in the memory.

10. a kind of computer storage media, which is characterized in that the calculating for being stored as used in above-mentioned shopping information pusher Machine software instruction, it includes be the program designed by shopping information pusher for executing above-mentioned aspect.