CN110298716A - Information-pushing method and device - Google Patents
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- CN110298716A CN110298716A CN201810240446.XA CN201810240446A CN110298716A CN 110298716 A CN110298716 A CN 110298716A CN 201810240446 A CN201810240446 A CN 201810240446A CN 110298716 A CN110298716 A CN 110298716A
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
- G06Q30/0631—Recommending goods or services
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- H—ELECTRICITY
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- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
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- H04L67/55—Push-based network services
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Abstract
The embodiment of the present application discloses information-pushing method and device.One specific embodiment of this method includes: to obtain the current search request of user, and searching request includes the identification information of article to be searched；At least one similar article similar to article to be searched is determined from the similar article set obtained in advance, the identification information of the identification information of the multiple articles of associated storage and similar article similar to each article in similar article set；Based on the similarity between article to be searched and similar article, the similar article of target is determined from similar article, wherein, in the historical behavior record of the similarity and multiple users of similar article and article to be searched, difference at the time of implementing user behavior at the time of same subscriber implements user behavior to similar article and to article to be searched is negatively correlated；The identification information of the similar article of target is pushed to user.The embodiment makes the pushed information pushed to user while guaranteeing precision, also improves the coverage of pushed information.
Description
Technical Field
The embodiment of the application relates to the technical field of computers, in particular to the technical field of internet, and particularly relates to a method and a device for pushing information.
Background
With the rapid development of the internet and the e-commerce industry, more and more users choose to shop online. The user can conveniently select the needed articles by accessing the electronic commerce website through the browser.
In many cases, the e-commerce web site will recommend items to the user, for example, recommending items related to the items in the records to the user through browsing records, shopping cart records, and purchase records of the user. Through item recommendation, on one hand, sales volume of an e-commerce website can be increased, and on the other hand, the active recommendation can avoid unnecessary search requests generated by frequent search and search of a user, so that burden of a website server is reduced.
Disclosure of Invention
The embodiment of the application provides an information pushing method and device.
In a first aspect, an embodiment of the present application provides an information pushing method, where the method includes: acquiring a current search request of a user, wherein the search request comprises identification information of an article to be searched; determining at least one similar article similar to the article to be searched from a pre-obtained similar article set, wherein the similar article set stores identification information of a plurality of articles and identification information of similar articles similar to each article in a related manner; determining a target similar article from the similar articles based on the similarity between the article to be searched and the similar articles, wherein the similarity between the similar article and the article to be searched is negatively correlated with the difference between the time when the same user implements the user behavior on the similar article and the time when the same user implements the user behavior on the article to be searched in historical behavior records of a plurality of users; and pushing the identification information of the target similar item to the user.
In some embodiments, after obtaining the current search request of the user, before determining at least one similar item similar to the item to be searched from the pre-obtained similar item set, the method further comprises: determining the article category to which the article to be searched belongs; and determining at least one similar item similar to the item to be searched from the pre-acquired similar item set, wherein the method comprises the following steps: and determining at least one similar item similar to the item to be searched from a similar item set which is obtained in advance and corresponds to the determined item category.
In some embodiments, for any item in the set of similar items, a similar item that is similar to the item is determined based on: for any user in the plurality of users, the following candidate similar item acquisition operations are performed on the user: acquiring information of user behaviors of a user on a plurality of articles in each preset statistical period, wherein the information of the user behaviors comprises operation types of operations of the user on any article and corresponding moments; determining a candidate similar item corresponding to the item based on the user behavior; determining the similarity between each candidate similar item and the item based on the candidate similar item corresponding to each user in the plurality of users and the time of each user operating each candidate similar item; determining at least one similar item similar to the item based on the similarity between each candidate similar item and the item.
In some embodiments, obtaining information of user behaviors performed on the plurality of items by the user in each of a plurality of preset statistical periods comprises: and acquiring information of user behaviors performed by the user on the plurality of articles through at least one terminal in each statistical period.
In some embodiments, for any user, a candidate similar item corresponding to the user is determined based on the following steps: for any item, determining a weight of any operation performed by the user on the item; taking the accumulated sum of the weights respectively corresponding to a plurality of operations performed on the article by the user as the weight corresponding to the article; and determining the articles with the corresponding weights larger than a preset weight threshold value as candidate similar articles.
In some embodiments, the similarity between any two similar items in the set of similar items is inversely related to the number of candidate similar items corresponding to users that have performed user behavior on both of the items.
In some embodiments, the similarity between any two similar items in the set of similar items is positively correlated with the number of users who implemented user actions on both of the two items, and negatively correlated with the product of the number of users who implemented user actions on each of the two items, respectively.
In a second aspect, an embodiment of the present application provides an information pushing apparatus, where the apparatus includes: the device comprises an acquisition unit, a search unit and a search unit, wherein the acquisition unit is configured to acquire a current search request of a user, and the search request comprises identification information of an article to be searched; the system comprises a first determining unit, a second determining unit and a searching unit, wherein the first determining unit is used for determining at least one similar article similar to an article to be searched from a similar article set acquired in advance, and the similar article set stores identification information of a plurality of articles and identification information of similar articles similar to the articles in a related mode; the second determining unit is configured to determine a target similar item from the similar items based on the similarity between the item to be searched and the similar items, wherein the similarity between the similar items and the item to be searched is negatively correlated with the difference between the time when the same user implements the user action on the similar items and the time when the same user implements the user action on the item to be searched in historical action records of a plurality of users; and the pushing unit is configured for pushing the identification information of the target similar item to the user.
In some embodiments, the information pushing apparatus further includes a third determining unit configured to: after the acquisition unit acquires a current search request of a user, before the first determination unit determines at least one similar item similar to the item to be searched from the pre-acquired similar item set, determining the item type of the item to be searched; and the second determining unit is further configured to: and determining at least one similar item similar to the item to be searched from a similar item set which is obtained in advance and corresponds to the determined item category.
In some embodiments, the information pushing device further includes a similar item acquiring unit configured to, for any item in the similar item set, determine a similar item similar to the item based on the following steps: for any user in the plurality of users, the following candidate similar item acquisition operations are performed on the user: acquiring information of user behaviors of a user on a plurality of articles in each preset statistical period, wherein the information of the user behaviors comprises operation types of operations of the user on any article and corresponding moments; determining a candidate similar item corresponding to the item based on the user behavior; determining the similarity between each candidate similar item and the item based on the candidate similar item corresponding to each user in the plurality of users and the time of each user operating each candidate similar item; determining at least one similar item similar to the item based on the similarity between each candidate similar item and the item.
In some embodiments, the similar item acquisition unit is further configured to: and acquiring information of user behaviors performed by the user on the plurality of articles through at least one terminal in each statistical period.
In some embodiments, the similar item acquiring unit is further configured to determine, for any user, a candidate similar item corresponding to the user based on the following steps: for any item, determining a weight of any operation performed by the user on the item; taking the accumulated sum of the weights respectively corresponding to a plurality of operations performed on the article by the user as the weight corresponding to the article; and determining the articles with the corresponding weights larger than a preset weight threshold value as candidate similar articles.
In some embodiments, the similarity between any two similar items in the set of similar items is inversely related to the number of candidate similar items corresponding to users that have performed user behavior on both of the items.
In some embodiments, the similarity between any two similar items in the set of similar items is positively correlated with the number of users who implemented user actions on both of the two items, and negatively correlated with the product of the number of users who implemented user actions on each of the two items, respectively.
In a third aspect, an embodiment of the present application provides a server, where the server includes: one or more processors; a storage device for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to implement the method as described in any implementation manner of the first aspect.
In a fourth aspect, the present application provides a computer-readable medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the method as described in any implementation manner of the first aspect.
According to the information pushing method and device provided by the embodiment of the application, the current search request of the user is obtained, at least one similar article similar to the article to be searched is determined from the pre-obtained similar article set, the target similar article is determined from the similar articles based on the similarity between the article to be searched and the similar article, and finally the identification information of the target similar article is pushed to the user. Therefore, the push information pushed to the user is ensured to be accurate, and meanwhile, the coverage of the push information is increased.
Drawings
Other features, objects and advantages of the present application will become more apparent upon reading of the following detailed description of non-limiting embodiments thereof, made with reference to the accompanying drawings in which:
FIG. 1 is an exemplary system architecture diagram in which the present application may be applied;
FIG. 2 is a flow diagram of one embodiment of an information push method according to the present application;
FIG. 3 is a schematic flow chart of obtaining similar items in a similar collection according to the present application;
FIG. 4 is a flow diagram of yet another embodiment of an information push method according to the present application;
FIG. 5 is a schematic diagram of an embodiment of an information pushing device according to the present application;
FIG. 6 is a schematic block diagram of a computer system suitable for use in implementing a server according to embodiments of the present application.
Detailed Description
The present application will be described in further detail with reference to the following drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the relevant invention and not restrictive of the invention. It should be noted that, for convenience of description, only the portions related to the related invention are shown in the drawings.
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.
Fig. 1 shows an exemplary system architecture 100 to which embodiments of the information pushing method or information pushing apparatus of the present application may be applied.
As shown in fig. 1, the system architecture 100 may include terminal devices 101, 102, 103, a network 104, and a server 105. The network 104 serves as a medium for providing communication links between the terminal devices 101, 102, 103 and the server 105. Network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few.
The user may use the terminal devices 101, 102, 103 to interact with the server 105 via the network 104 to receive or send messages or the like. The terminal devices 101, 102, 103 may have various client applications installed thereon, such as a web browser application, a shopping-type application, a search-type application, an instant messaging tool, and the like.
The terminal devices 101, 102, 103 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, e-book readers, MP3 players (Moving Picture experts Group Audio Layer III, mpeg compression standard Audio Layer 3), MP4 players (Moving Picture experts Group Audio Layer IV, mpeg compression standard Audio Layer 4), laptop portable computers, desktop computers, and the like.
The server 105 may be a server providing various services, such as a background server providing support for shopping-like applications displayed on the terminal devices 101, 102, 103. The background server may analyze and perform other processing on the received data such as the search request, and feed back a processing result (e.g., push information) to the terminal device.
It should be noted that the information pushing method provided in the embodiment of the present application is generally executed by the server 105, and accordingly, the information pushing apparatus is generally disposed in the server 105.
The server 105 may be hardware or software. When the server 105 is hardware, it may be implemented as a distributed server cluster composed of a plurality of servers, or may be implemented as a single server. When the server 105 is software, it may be implemented as multiple pieces of software or software modules (e.g., to provide distributed services), or as a single piece of software or software module. And is not particularly limited herein.
It should be understood that the number of terminal devices, networks, and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
With continued reference to FIG. 2, a flow 200 of one embodiment of an information push method according to the present application is shown. The information pushing method comprises the following steps:
step 201, obtaining a current search request of a user, where the search request includes identification information of an item to be searched.
In this embodiment, an execution subject of the information push method (for example, a server shown in fig. 1) may receive a current search request of a user from a terminal with which the user browses item information through a wired connection manner or a wireless connection manner. Wherein, the search request comprises the identification information of the item to be searched. In some application scenarios, the executing entity of the information pushing method may obtain the current search request of the user from a server providing item information search service to the user through a wired connection manner or a wireless connection manner.
Typically, a user may purchase items over the internet using a shopping-like application installed on the terminal. At this time, the user may initiate a search request to the server of the shopping application by entering identification information of the item to be searched in a search box in the shopping application. In this embodiment, the identification information of the item to be searched may include a full name indicating the item to be searched, an abbreviation indicating the item to be searched, and the like.
Step 202, at least one similar item similar to the item to be searched is determined from the pre-acquired similar item set, and the identification information of the plurality of items and the identification information of the similar items similar to the items are stored in the similar item set in a correlated manner.
In this embodiment, based on the current search request of the user obtained in step 201, the executing entity (for example, the server shown in fig. 1) may determine at least one similar item similar to the item to be searched from the pre-acquired similar item set.
The similar item set stores identification information of a plurality of items and identification information of similar items similar to the items. That is, the execution body stores in advance identification information of at least one similar item corresponding to each item.
In some optional implementations of this embodiment, for any item in the similar item set, a similar item in the similar item set that is similar to the item may be obtained based on the flow 300 shown in fig. 3:
step 301, for any user in a plurality of users, performing the following candidate similar item acquisition operations for the user: acquiring information of user behaviors of a user on a plurality of articles in each preset statistical period, wherein the information of the user behaviors comprises operation types of operations of the user on any article and corresponding moments; candidate similar items corresponding to the item are determined based on the user behavior.
In these optional implementations, the execution subject may obtain a large amount of historical internet behavior records of a plurality of users from a predetermined database, and distinguish user behavior records of different users from the large amount of historical internet behavior records. The predetermined database may be a database for storing historical internet behavior records of a large number of users.
After obtaining the user behavior records of different users, for any one of the users, the electronic device may obtain, from the user behavior record, information of the user behavior, which is implemented by the user on the plurality of articles in each of a plurality of preset statistical periods. Each statistical cycle herein may comprise a predetermined time period, and two adjacent statistical cycles may comprise repeated time periods. For example, the period from 7 th natural day to 1 st natural day on the current date may be divided into 5 statistical periods, each statistical period includes 3 natural days, and two adjacent statistical periods may include 2 repeated natural days. That is, {7,6,5}, {6,5,4}, {5,4,3}, {4,3,2}, {3,2,1}, where 1, 2, 3, 4, 5, 6, 7 are the numbers of the natural days apart from the current date, respectively.
In this embodiment, the information on the user behavior includes information on the operation type of the operation performed by the user on any article and information on the corresponding time. Here, the operation category of the operation performed by the user on any article may include at least one of: clicking on a detailed information page of the item, clicking on an image and text in the detailed information page of the item, clicking on an evaluation of the item, browsing on a detailed information page of the item, browsing duration, adding a shopping cart, focusing on, consulting, searching and browsing on a detailed information page of the item, and the like.
The execution body may count, in any one statistical period, the identification information of the operation category in which the user performs each operation on the plurality of articles and the time at which the user performs each operation on each article, with three natural days as one statistical period. The executive may analyze the user's behavior over a plurality of statistical periods by various methods to determine candidate similar items corresponding to the user.
Further optionally, for any user of the multiple users, the electronic device may determine a candidate similar item corresponding to the user based on the following steps: first, for any item, the weight of any operation performed by the user on the item is determined. Next, the sum of the weights respectively corresponding to the plurality of operations performed by the user on the item is used as the weight corresponding to the item. And finally, determining the articles with the corresponding weights larger than a preset weight threshold value as candidate similar articles. That is, for any item, the executing agent may determine a weight of any operation performed by the user on the item. The weight of any operation may be preset by the electronic device, or may be a weight corresponding to the operation type counted by the execution subject according to a large amount of internet user behavior records. For example, for any operation category, in a statistical period, the ratio of the number of users who perform the operation of the category and have performed the ordering operation on the article performing the operation of the category to the total number of users performing the operation category is used as the weight corresponding to the operation category. The electronic device may determine, as the weight corresponding to the item, an accumulated sum of weights corresponding to each of a plurality of operation types performed by the user for the item. The executing agent may determine the item with the corresponding weight greater than the preset weight threshold as the candidate similar item.
Further optionally, the obtaining information of the user behavior performed by the user on the plurality of articles in each of the plurality of preset statistical periods includes: and acquiring information of user behaviors performed by the user on the plurality of articles through at least one terminal in each statistical period. That is, the electronic device may count information on operations performed by one user on a plurality of articles through different terminals. The terminal herein may include: smart phones, tablet computers, laptop portable computers, desktop computers, and the like.
Step 302, determining the similarity between each candidate similar item and the item based on the candidate similar item corresponding to each user in the plurality of users and the time when each user operates each candidate similar item.
Here, when the same user performs the operation of the same category on one candidate similar item a plurality of times, the analysis may be performed in accordance with the operation of the category once closest to the current date.
In these optional implementations, for the item, the execution subject determines the similarity between each candidate similar item and the item at the time of the operation performed on each candidate similar item by each user and the candidate similar item by each user. The similarity between the item and the similar items is negatively correlated with the difference between the time when the same user conducts the user action on the similar items and the time when the same user conducts the user action on the items to be searched in the historical action records of the multiple users. That is, for the item to be searched, the similarity between the corresponding similar item and the item to be searched is inversely related to the difference between the time when the similar item is operated by the same user and the time when the item to be searched is operated by the same user in the historical behavior records of the multiple users.
Optionally, the similarity between any two similar items in the similar item set is inversely related to the number of candidate similar items corresponding to the user who performed the user behavior on both of the two items.
Further optionally, the similarity between any two similar items in the similar item set is positively correlated with the number of users who have implemented user behaviors on both of the two items, and is negatively correlated with the product of the numbers of users who have implemented user behaviors on each of the two items.
As an example, the similarity between any two similar items in the above similar item set may be calculated according to the following formula:
wherein,
r is the similarity between the article A and the article B; m is the number of users who have implemented user actions on both the article A and the article B, and M is a positive integer greater than 1; u is a positive integer, and u is more than or equal to 1 and less than or equal to M; n (a) is the number of users who performed user actions on item a, and n (B) is the number of users who performed user actions on item B; n (u) is the total of candidate similar articles corresponding to the u-th user who implements user behaviors on both the article A and the article BThe number of the particles; α and β are predetermined coefficients; t isAThe time T of user action on article A for the u-th user who performed user action on both article A and article BBThe time at which the user action is performed on the item B by the user who performed the user action on both the item a and the item B is the u-th.
Step 303, determining at least one similar item similar to the item based on the similarity between each candidate similar item and the item.
In these alternative implementations, the execution subject may regard at least one item having a similarity greater than a preset similarity threshold as an item similar to the item. Or selecting a plurality of similar articles with the serial numbers smaller than the preset serial number as articles similar to the article from the similar article sequence obtained by sequencing the similarity of the articles from big to small.
In this way, for any item, the execution subject may obtain in advance identification information of at least one similar item similar to the item.
Step 203, determining the target similar articles from the similar articles based on the similarity between the articles to be searched and the similar articles.
In this embodiment, the execution main body of the information push method may further determine the target similar item from the items similar to the item to be searched according to the similarity between the item to be searched and each similar item. The execution main body can select at least one target similar item which meets the quantity limit and is similar to the item to be searched from a plurality of similar items which are similar to the item to be searched according to the quantity limit of the pushed information. For example, at least one target similar item is selected from a plurality of items similar to the item to be searched in the order of the similarity from large to small.
And step 204, pushing the identification information of the target similar item to the user.
In this embodiment, the execution subject may push the identification information of the target similar item obtained by the execution subject in step 203 to the user while returning the search result to the user.
The method provided by the above embodiment of the application obtains the current search request of the user, then determines at least one similar item similar to the item to be searched from the pre-obtained similar item set, then determines the target similar item from the similar items based on the similarity between the item to be searched and the similar item, and finally pushes the identification information of the target similar item to the user. Because the articles in the similar article set are obtained by statistics from the candidate similar articles respectively corresponding to different users, the push information pushed to the users is ensured to be accurate, and meanwhile, the coverage of the push information is increased.
With further reference to fig. 4, a flow 400 of yet another embodiment of an information push method is shown. The process 400 of the information pushing method includes the following steps:
step 401, a current search request of a user is obtained, where the search request includes identification information of an item to be searched.
Step 402, determining the item category to which the item to be searched belongs.
In this embodiment, for an item to be searched included in a current search request of a user, an execution subject (for example, a server shown in fig. 1) of the information push method may determine an item category to which the item to be searched belongs based on a plurality of history search records corresponding to the item to be searched. Specifically, the item category to which the item to be searched in the current search request belongs may be determined according to a ratio of users who have performed selection operations on search results of different item categories corresponding to the item to be searched, which are described in the history search record, for example, for an item to be searched "apple" included in the current search request of the user, the category corresponding to the item to be searched "apple" may include "mobile terminal" and "fruit" in the history search record including the "apple". On the other hand, if the percentage of users who have performed the click operation on the search result corresponding to the category of the "mobile terminal" in the history search log is 60%, the category of the item to which the "apple" included in the current search request of the user belongs may be determined as the "mobile terminal". Alternatively, the category to which the item to be searched belongs may be determined according to the category of the item to be searched indicated in the search request by the user. For example, when the user inputs "apple" in the search bar for searching, the item category corresponding to the item to be searched can be designated as fruit. The executing body may determine the item category corresponding to the item to be searched for, by using the item category "fruit" indicating "apple" in the search request.
And step 403, determining at least one similar item similar to the item to be searched from a similar item set which is obtained in advance and corresponds to the determined item type.
In this embodiment, the executing body may determine at least one similar item similar to the item to be searched from a similar item set corresponding to a category to which the item to be searched belongs, where the similar item set is acquired in advance. That is, similar article sets corresponding to different types of articles may be preset in the execution main body. For each category, the execution main body may obtain and store at least one similar article corresponding to each article in the category in advance.
Further, for any item in an item category, the executing entity may obtain a similar item of the item by:
firstly, for any user in a plurality of users, the following candidate similar item acquisition operations are performed on the user: acquiring information of user behaviors of the user on a plurality of articles in the article category in each statistical period; candidate similar items corresponding to the item are determined based on the user behavior.
Secondly, determining the similarity between each candidate similar item and the item based on the candidate similar item corresponding to each user in the plurality of users and the time of operating each candidate similar item.
Finally, at least one similar item similar to the item is determined based on the similarity between each candidate similar item and the item.
For the above detailed steps of obtaining similar items of an item in an item category, reference may be made to the related description of the flow 300 shown in fig. 3, and details thereof are not repeated here.
In these alternative implementations, the execution subject may regard at least one item with a similarity greater than a preset similarity threshold as at least one similar item similar to the item. Or selecting a plurality of similar articles with the serial numbers smaller than the preset serial number as at least one similar article similar to the article from the similar article sequence obtained by sequencing the similarity of the similar articles from big to small.
And step 404, determining a target similar item from the similar items based on the similarity between the item to be searched and the similar items.
Step 405, pushing identification information of the target similar item to the user.
It is worth pointing out that when the quantity of the target similar items obtained from the method is less than the preset quantity of the items pushed to the user, the hot items and the newly introduced items in the same category as the items to be searched can be selected for supplement. In some application scenarios, the search may also be supplemented from hot items and newly introduced items in a plurality of categories related to the category to which the item to be searched belongs.
As can be seen from fig. 4, compared with the embodiment corresponding to fig. 2, the flow 400 of the information pushing method in this embodiment highlights a step of obtaining a similar item set corresponding to each item category according to the item category in advance, where the execution subject may determine the item category corresponding to the item to be searched, and determine a target similar item from the similar item set corresponding to the item category, and thus, the scheme described in this embodiment may further improve the accuracy of the generated pushed information.
With further reference to fig. 5, as an implementation of the method shown in the above-mentioned figures, the present application provides an embodiment of an information pushing apparatus, which corresponds to the embodiment of the method shown in fig. 2, and which can be applied in various electronic devices.
As shown in fig. 5, the information pushing apparatus 500 of the present embodiment includes: an acquisition unit 501, a first determination unit 502, a second determination unit 503, and a push unit 504. The obtaining unit 501 is configured to obtain a current search request of a user, where the search request includes identification information of an item to be searched; a first determining unit 502, configured to determine at least one similar item similar to an item to be searched from a pre-obtained similar item set, where identification information of a plurality of items and identification information of similar items similar to each item are stored in the similar item set in an associated manner; a second determining unit 503, configured to determine a target similar item from the similar items based on a similarity between the item to be searched and the similar items, where the similarity between the similar item and the item to be searched is negatively correlated with a difference between a time when the same user performs a user action on the similar item and a time when the same user performs a user action on the item to be searched in historical action records of multiple users; a pushing unit 504 configured to push the identification information of the target similar item to the user.
In this embodiment, specific processes of the obtaining unit 501, the first determining unit 502, the second determining unit 503, and the pushing unit 504 of the information pushing apparatus 500 and technical effects brought by the specific processes can refer to related descriptions of step 201, step 202, step 203, and step 204 in the corresponding embodiment of fig. 2, which are not repeated herein.
In some optional implementations of the present embodiment, the information pushing apparatus 500 further includes a third determining unit (not shown in the figure), and the third determining unit is configured to: after the acquisition unit acquires a current search request of a user, before the first determination unit determines at least one similar item similar to the item to be searched from the pre-acquired similar item set, determining the item type of the item to be searched; and the second determining unit is further configured to: and determining at least one similar item similar to the item to be searched from a similar item set which is obtained in advance and corresponds to the determined item category.
In some optional implementations of the present embodiment, the information pushing apparatus 500 further includes a similar item acquiring unit 505. The similar item acquisition unit 505 is configured to determine, for any item, a similar item in the similar item set based on the following steps: firstly, for any user in a plurality of users, the following candidate similar item acquisition operations are performed on the user: acquiring information of user behaviors of a user on a plurality of articles in each preset statistical period, wherein the information of the user behaviors comprises operation types of operations of the user on any article and corresponding moments; determining a candidate similar item corresponding to the item based on the user behavior; secondly, determining the similarity between each candidate similar article and the article based on the candidate similar article corresponding to each user in the plurality of users and the time of each user operating each candidate similar article; finally, at least one similar item similar to the item is determined based on the similarity between each candidate similar item and the item.
In some optional implementations of the present embodiment, the similar item acquiring unit 505 is further configured to: and acquiring information of user behaviors performed by the user on the plurality of articles through at least one terminal in each statistical period.
In some optional implementations of the present embodiment, the similar item acquiring unit 505 is further configured to, for any user, determine a candidate similar item corresponding to the user based on the following steps: for any item, determining a weight of any operation performed by the user on the item; taking the accumulated sum of the weights respectively corresponding to a plurality of operations performed on the article by the user as the weight corresponding to the article; and determining the articles with the corresponding weights larger than a preset weight threshold value as candidate similar articles.
In some optional implementations of this embodiment, the similarity between any two similar items in the set of similar items is inversely related to the number of candidate similar items corresponding to the user who performed the user behavior on both of the two items.
In some optional implementation manners of this embodiment, the similarity between any two similar items in the similar item set is positively correlated with the number of users who have implemented user behaviors on both of the two items, and is negatively correlated with the product of the numbers of users who have implemented user behaviors on each of the two items, respectively.
As an example, the similar item obtaining unit 505 may be configured to calculate a similarity between any two similar items in the similar item set according to the following formula:
wherein,
r is the similarity between the article A and the article B; m is the number of users who have implemented user actions on both the article A and the article B, and M is a positive integer greater than 1; u is a positive integer, and u is more than or equal to 1 and less than or equal to M; n (a) is the number of users who performed user actions on item a, and n (B) is the number of users who performed user actions on item B; n (u) is the total number of candidate similar articles corresponding to the u-th user who performed user behavior on both article a and article B; α and β are predetermined coefficients; t isAThe time T of user action on article A for the u-th user who performed user action on both article A and article BBThe time at which the user action is performed on the item B by the user who performed the user action on both the item a and the item B is the u-th.
Referring now to FIG. 6, shown is a block diagram of a computer system 600 suitable for use in implementing a server according to embodiments of the present application. The server shown in fig. 6 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present application.
As shown in fig. 6, the computer system 600 includes a Central Processing Unit (CPU)601, which can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM) 602 or a program loaded from a storage section 608 into a Random Access Memory (RAM) 603. In the RAM 603, various programs and data necessary for the operation of the system 600 are also stored. The CPU 601, ROM602, and RAM 603 are connected to each other via a bus 604. An Input/Output (I/O) interface 605 is also connected to bus 604.
The following components are connected to the I/O interface 605: an input portion 606 including a keyboard, a mouse, and the like; an output section 607 including a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, a speaker, and the like; a storage section 608 including a hard disk and the like; and a communication section 609 including a network interface card such as a LAN (Local area network) card, a modem, or the like. The communication section 609 performs communication processing via a network such as the internet. The driver 610 is also connected to the I/O interface 605 as needed. A removable medium 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 610 as necessary, so that a computer program read out therefrom is mounted in the storage section 608 as necessary.
In particular, according to an embodiment of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 609, and/or installed from the removable medium 611. The computer program performs the above-described functions defined in the method of the present application when executed by a Central Processing Unit (CPU) 601. It should be noted that the computer readable medium described herein can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present application, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In this application, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present application may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, or the like, as well as conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in the embodiments of the present application may be implemented by software or hardware. The described units may also be provided in a processor, and may be described as: a processor includes an acquisition unit, a first determination unit, a second determination unit, and a pushing unit. Where the names of these units do not in some cases constitute a limitation on the unit itself, for example, the obtaining unit may also be described as a "unit that obtains the user's current search request".
As another aspect, the present application also provides a computer-readable medium, which may be contained in the apparatus described in the above embodiments; or may be present separately and not assembled into the device. The computer readable medium carries one or more programs which, when executed by the apparatus, cause the apparatus to: acquiring a current search request of a user, wherein the search request comprises identification information of an article to be searched; determining at least one similar article similar to the article to be searched from a pre-obtained similar article set, wherein the similar article set stores identification information of a plurality of articles and identification information of similar articles similar to each article in a related manner; determining a target similar article from the similar articles based on the similarity between the article to be searched and the similar articles, wherein the similarity between the similar article and the article to be searched is negatively correlated with the difference between the time when the same user implements the user behavior on the similar article and the time when the same user implements the user behavior on the article to be searched in historical behavior records of a plurality of users; and pushing the identification information of the target similar item to the user.
The above description is only a preferred embodiment of the application and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the invention herein disclosed is not limited to the particular combination of features described above, but also encompasses other arrangements formed by any combination of the above features or their equivalents without departing from the spirit of the invention. For example, the above features may be replaced with (but not limited to) features having similar functions disclosed in the present application.
Claims (16)
1. An information push method, comprising:
acquiring a current search request of a user, wherein the search request comprises identification information of an article to be searched;
determining at least one similar article similar to the article to be searched from a pre-obtained similar article set, wherein the similar article set stores identification information of a plurality of articles and identification information of similar articles similar to each article in a related manner;
determining a target similar article from the similar articles based on the similarity between the article to be searched and the similar articles, wherein the similarity between the similar article and the article to be searched is negatively correlated with the difference between the time when the same user implements the user behavior on the similar article and the time when the same user implements the user behavior on the article to be searched in historical behavior records of a plurality of users;
and pushing the identification information of the target similar item to the user.
2. The method of claim 1, wherein after the obtaining of the current search request of the user, before the determining of the at least one similar item similar to the item to be searched from the pre-obtained set of similar items, the method further comprises:
determining the article category to which the article to be searched belongs; and
the determining at least one similar item similar to the item to be searched from the pre-acquired similar item set comprises:
and determining at least one similar item similar to the item to be searched from a similar item set which is obtained in advance and corresponds to the determined item category.
3. The method of claim 1, wherein, for any item in the collection of similar items, a similar item that is similar to the item is determined based on:
for any user in the plurality of users, the following candidate similar item acquisition operations are performed on the user: acquiring information of user behaviors of a user on a plurality of articles in each preset statistical period, wherein the information of the user behaviors comprises operation types of operations of the user on any article and corresponding moments; determining a candidate similar item corresponding to the item based on the user behavior;
determining the similarity between each candidate similar item and the item based on the candidate similar item corresponding to each user in the plurality of users and the time of operating each candidate similar item;
determining at least one similar item similar to the item based on the similarity between each candidate similar item and the item.
4. The method of claim 3, wherein the obtaining information of the user behavior performed by the user on the plurality of items in each of the plurality of preset statistical periods comprises:
and acquiring information of user behaviors performed by the user on the plurality of articles through at least one terminal in each statistical period.
5. The method of claim 3, wherein for any user, determining a candidate similar item corresponding to the user is based on:
for any item, determining a weight of any operation performed by the user on the item; taking the accumulated sum of the weights respectively corresponding to a plurality of operations performed on the article by the user as the weight corresponding to the article;
and determining the article with the corresponding weight larger than a preset weight threshold value as a candidate similar article.
6. The method of claim 5, wherein the similarity between any two similar items in the set of similar items is inversely related to the number of candidate similar items corresponding to users who have performed user actions on both of the items.
7. The method of claim 6, wherein the similarity between any two similar items in the set of similar items is positively correlated with the number of users performing user actions on both of the two items and negatively correlated with the product of the number of users performing user actions on each of the two items, respectively.
8. An information pushing apparatus comprising:
the device comprises an acquisition unit, a search unit and a search unit, wherein the acquisition unit is configured to acquire a current search request of a user, and the search request comprises identification information of an article to be searched;
a first determining unit, configured to determine at least one similar item similar to the item to be searched from a pre-obtained similar item set, where identification information of a plurality of items and identification information of similar items similar to each item are stored in the similar item set in an associated manner;
a second determining unit, configured to determine a target similar item from the similar items based on a similarity between the item to be searched and the similar items, where the similarity between the similar item and the item to be searched is negatively correlated with a difference between a time when a same user performs a user action on the similar item and a time when the same user performs a user action on the item to be searched in historical action records of multiple users;
and the pushing unit is configured to push the identification information of the target similar item to the user.
9. The apparatus of claim 8, wherein the apparatus further comprises a third determining unit,
the third determination unit is configured to: after the acquisition unit acquires a current search request of a user, before the first determination unit determines at least one similar item similar to the item to be searched from a pre-acquired similar item set, determining an item category to which the item to be searched belongs; and
the second determination unit is further configured to: and determining at least one similar item similar to the item to be searched from a similar item set which is obtained in advance and corresponds to the determined item category.
10. The apparatus according to claim 8, wherein the apparatus further comprises a similar item acquisition unit configured to determine, for any item in the set of similar items, a similar item similar to the item based on:
for any user in the plurality of users, the following candidate similar item acquisition operations are performed on the user: acquiring information of user behaviors of a user on a plurality of articles in each preset statistical period, wherein the information of the user behaviors comprises operation types of operations of the user on any article and corresponding moments; determining a candidate similar item corresponding to the item based on the user behavior;
determining the similarity between each candidate similar item and the item based on the candidate similar item corresponding to each user in the plurality of users and the time of each user operating each candidate similar item;
determining at least one similar item similar to the item based on the similarity between each candidate similar item and the item.
11. The apparatus according to claim 10, wherein the similar item acquisition unit is further configured for:
and acquiring information of user behaviors performed by the user on the plurality of articles through at least one terminal in each statistical period.
12. The apparatus according to claim 10, wherein the similar item acquiring unit is further configured to determine, for any user, a candidate similar item corresponding to the user based on the following steps:
for any item, determining a weight of any operation performed by the user on the item; taking the accumulated sum of the weights respectively corresponding to a plurality of operations performed on the article by the user as the weight corresponding to the article;
and determining the article with the corresponding weight larger than a preset weight threshold value as a candidate similar article.
13. The apparatus of claim 12, wherein the similarity between any two similar items in the set of similar items is inversely related to the number of candidate similar items corresponding to users who performed user actions on both of the items.
14. The apparatus of claim 13, wherein the similarity between any two similar items in the set of similar items is positively correlated with the number of users performing user actions on both of the two items and negatively correlated with the product of the number of users performing user actions on each of the two items, respectively.
15. An electronic device, comprising:
one or more processors;
a storage device for storing one or more programs,
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method of claims 1-7.
16. A computer-readable medium, on which a computer program is stored, which program, when being executed by a processor, carries out the method of claims 1-7.
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