CN106528851A - Intelligent recommendation method and device - Google Patents
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- CN106528851A CN106528851A CN201611062571.3A CN201611062571A CN106528851A CN 106528851 A CN106528851 A CN 106528851A CN 201611062571 A CN201611062571 A CN 201611062571A CN 106528851 A CN106528851 A CN 106528851A
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Abstract
The invention discloses an intelligent recommendation method and device. The method comprises the following steps: collecting browsing behavior data of a user and behavior data of the user in a relevant third-party application; according to the browsing behavior data and the behavior data in the relevant third-party application, creating a tag for the user, and storing a corresponding relationship between the user and the tag in a user tag library; and when the user triggers an information browsing operation, acquiring the tag corresponding to the user from the user tag library, and pushing information to the user according to the tag. The method and device provided by the invention has the advantages that intelligent recommendations can be carried out for the user based on various behaviors of the user, so that the intelligent recommendation effects are improved.
Description
Technical field
The present invention relates to data processing field, and in particular to a kind of intelligent recommendation method and device.
Background technology
Intelligent recommendation is to lift one of effective means of information reading experience, is aiming at different users in simple terms,
Its reading habit is analyzed, by setting up intelligent recommendation model, with intelligent recommendation algorithm, satisfaction is picked out from the media library of backstage
The information of user's request, video etc. are read for user.Intelligent recommendation model, intelligent recommendation algorithm in intelligent recommendation with being
It is no proper, it is directly connected to the quality of intelligent recommendation effect.
At present, simply intelligent recommendation is carried out according to the reading behavior of user for user, have some limitations, intelligently push away
The effect recommended has much room for improvement.
The content of the invention
The invention provides a kind of intelligent recommendation method and device, can carry out intelligence based on various behaviors of user for user
Can recommend, improve the effect of intelligent recommendation.
A kind of Feature Selection method that the present invention is provided, methods described include：
Collect the navigation patterns data of user, and the behavioral data in interested third party application；
With reference to the navigation patterns data and the behavioral data in the interested third party application, it is user's life
Into label；The user is stored in user tag storehouse with the corresponding relation of the label；
When user's triggering information browing is operated, the corresponding label of the user is obtained from the user tag storehouse, and
It is that the user pushes information according to the label.
Preferably, methods described also includes：
With reference to the navigation patterns data and the behavioral data in the interested third party application, it is the user
During generating label, it is that the label determines weighted value, the weighted value is used for determining the corresponding information of the label
Push order；
When the user is browsed to the information for pushing, navigation patterns number of the user to the information is collected
According to；
According to navigation patterns data of the user to the information, the weighted value of the label is adjusted.
Preferably, the navigation patterns data include clicking on behavioral data, browse duration data, browse range data.
Preferably, the interested third party application includes online game application, the behavior in the interested third party application
Data include the map information residing for the user, people information that the user has, weapon information.
Preferably, navigation patterns data described in the combination and the behavioral data in the interested third party application, be
The user generates label, including：
Respectively described navigation patterns data and the behavioral data in the interested third party application arrange weighted value；
According to the navigation patterns data and the behavioral data in the interested third party application, and combine the power
Weight values, are that the user generates label.
Present invention also offers a kind of intelligent recommendation device, described device includes：
First collection module, for collecting the navigation patterns data of user, and the behavior in interested third party application
Data；
Generation module, for reference to the navigation patterns data and the behavior number in the interested third party application
According to being that the user generates label；
Memory module, for the user is stored in user tag storehouse with the corresponding relation of the label；
Acquisition module, for when user's triggering information browing is operated, obtaining the user from the user tag storehouse
Corresponding label；
Pushing module, for pushing information according to the label for the user.
Preferably, described device also includes：
Determining module, for reference to the navigation patterns data and the behavior number in the interested third party application
According to it, during the user generates label, is that the label determines weighted value to be, the weighted value is used for determining the label
The push order of corresponding information；
Second collection module, for when the user is browsed to the information for pushing, collecting the user to described
The navigation patterns data of information；
Adjusting module, for the navigation patterns data according to the user to the information, adjusts the weight of the label
Value.
Preferably, the navigation patterns data include clicking on behavioral data, browse duration data, browse range data.
Preferably, the interested third party application includes online game application, the behavior in the interested third party application
Data include the map information residing for the user, people information that the user has, weapon information.
Preferably, the generation module, including：
Submodule is set, for being respectively the navigation patterns data and the behavior in the interested third party application
Data arrange weighted value；
Submodule is generated, for according to the navigation patterns data and the behavior number in the interested third party application
According to, and the weighted value is combined, it is that the user generates label.
In the intelligent recommendation method that the present invention is provided, first, the navigation patterns data of user are collected, and in correlation the 3rd
Behavioral data in Fang Yingyong.Secondly, with reference to the navigation patterns data and the behavior in the interested third party application
Data, are that the user generates label, and the user are stored in user tag storehouse with the corresponding relation of the label.When
When user's triggering information browing is operated, the corresponding label of the user is obtained from the user tag storehouse, and according to the mark
Sign information is pushed for the user.The present invention can carry out intelligent recommendation based on various behaviors of user for user, improve intelligence
The effect of recommendation.
Description of the drawings
For the technical scheme being illustrated more clearly that in the embodiment of the present application, below will be to making needed for embodiment description
Accompanying drawing is briefly described, it should be apparent that, drawings in the following description are only some embodiments of the present application, for
For those of ordinary skill in the art, without having to pay creative labor, can be obtaining which according to these accompanying drawings
His accompanying drawing.
A kind of intelligent recommendation method flow diagram that Fig. 1 is provided for the present invention；
Another kind of intelligent recommendation method flow diagram that Fig. 2 is provided for the present invention；
A kind of signaling of intelligent recommendation method for being applied to online game information browing function that Fig. 3 is provided for the present invention is handed over
Mutually scheme；
A kind of intelligent recommendation apparatus structure schematic diagram that Fig. 4 is provided for the present invention；
A kind of part-structure schematic diagram of computer that Fig. 5 is provided for the present invention.
Specific embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present application, the technical scheme in the embodiment of the present application is carried out clear, complete
Site preparation is described, it is clear that described embodiment is only some embodiments of the present application, rather than the embodiment of whole.It is based on
Embodiment in the application, it is every other that those of ordinary skill in the art are obtained under the premise of creative work is not made
Embodiment, belongs to the scope of the application protection.
With reference to Fig. 1, it is a kind of intelligent recommendation method flow diagram provided in an embodiment of the present invention, methods described can specifically be wrapped
Include：
S101：Collect the navigation patterns data of user, and the behavioral data in interested third party application.
Intelligent recommendation is that the label based on user carries out intelligent recommendation for user, and the generation method of the label of user is direct
Affect the effect of intelligent recommendation.As behavior of the user in interested third party application can also reflect the hobby of user, institute
With, in order to improve satisfaction of the user to intelligent recommendation result, in the embodiment of the present invention for user label generating process,
It is not only relevant with the navigation patterns of user, and the behavior with user in interested third party application is relevant.
In practical operation, system can collect the navigation patterns data of user, it may for example comprise user is produced in navigation process
Click behavioral data, browse duration data, browse range data etc..Meanwhile, system can also collect user the related 3rd
Behavioral data in Fang Yingyong, wherein, interested third party application is the third-party application relevant with the navigation patterns of user.Example
Such as, user when browse network plays relevent information, online game application is interested third party application, and system will collect user and exist
Behavioral data in online game application.In addition, the interested third party application can be multiple applications.
S102：With reference to the navigation patterns data and the behavioral data in the interested third party application, it is described
User generates label.
In the embodiment of the present invention, system is in the navigation patterns data for collecting user and in interested third party application
After behavioral data, with reference to the navigation patterns data and the behavioral data in the interested third party application, it is the use
Family generates label.
In a kind of preferred implementation, navigation patterns data respectively described first and in the interested third party application
In behavioral data arrange weighted value.Specifically, the behavioral data in different interested third party applications, can be according to user
Demand is respectively provided with different weighted values.Then, according to the navigation patterns data and in the interested third party application
Behavioral data, and combine the weighted value, be that the user generates label.Specifically, exist in practical application a variety of real
Existing mode, will not be described here.
S103：The user is stored in user tag storehouse with the corresponding relation of the label.
In the embodiment of the present invention, after label being generated for user, user is stored in into user's mark with the corresponding relation of label
Sign in storehouse, specifically, a user there can be multiple labels.
In addition, the embodiment of the present invention can also arrange corresponding weight for each label stored in the user tag storehouse
Value, wherein weighted value can be realized in the form of scoring.When information is pushed for user, can be according to the corresponding power of each label
Weight values determine the push order of the corresponding information of each label.Specifically, the corresponding information of the higher label of weighted value can be with excellent
It is first pushed.
S104：When user's triggering information browing is operated, the corresponding mark of the user is obtained from the user tag storehouse
Sign, and be that the user pushes information according to the label.
In the embodiment of the present invention, when user's triggering information browing operation, such as, when opening information browing application, system can be from
The corresponding label of active user is obtained in user tag storehouse.After the label is got, according to the label in backstage information
Inquire about corresponding information in data base, and by the message push to client so that user browses.
In intelligent recommendation method provided in an embodiment of the present invention, first, the navigation patterns data of user are collected, and in phase
Close the behavioral data in third-party application.Secondly, with reference to the navigation patterns data and in the interested third party application
Behavioral data, be that the user generates label, and the user be stored in into user tag with the corresponding relation of the label
In storehouse.When user's triggering information browing is operated, the corresponding label of the user is obtained from the user tag storehouse, and according to
The label is that the user pushes information.The embodiment of the present invention can carry out intelligence based on various behaviors of user for user and push away
Recommend, improve the effect of intelligent recommendation.
The embodiment of the present invention additionally provides a kind of intelligent recommendation method, with reference to Fig. 2, is provided in an embodiment of the present invention another
Plant intelligent recommendation method flow diagram.Methods described includes：
S201：Collect the navigation patterns data of user, and the behavioral data in interested third party application.
S202：With reference to the navigation patterns data and the behavioral data in the interested third party application, it is described
User's generation label, and determine the weighted value of each label, the weighted value is used for determining the corresponding information of the label
Push order.
As a user can have multiple labels, so the order in order to determine message push, the embodiment of the present invention
It is it is determined that during label, true with reference to the navigation patterns data and the behavioral data in the interested third party application
The weighted value of fixed each label, pushes the higher corresponding money of label of weighted value so as to preferential when information is pushed for the user
News.
In practical application, if the user has two labels a, b, weighted value is respectively 10 and 20.As the user
After having read the article of certain tape label a, the weighted value of a can Jia 1；When the user is in interested third party application, such as network
Certain behavior has been carried out in game, has such as been bought, if the behavior is relevant with label b, the weighted value of label b has been added 1.Such as
It is such, finally give the corresponding weighted value of each label of the user.
S203：The user is stored in user tag storehouse with the corresponding relation of the label.
S204：When user's triggering information browing is operated, the corresponding mark of the user is obtained from the user tag storehouse
Sign, and be that the user pushes information according to the label.
S205：When the user is browsed to the information for pushing, collect the user and row is browsed to the information
For data.
S206：According to navigation patterns data of the user to the information, the weighted value of the label is adjusted.
In order to know the effect of intelligent recommendation in time, the embodiment of the present invention after information is pushed to user, real-time collecting institute
Navigation patterns data of the user to the information are stated, including the click behavior to the recommended information, duration is browsed, is browsed scope
Deng, and according to the navigation patterns data point reuse to the information collected label weighted value, upper to be once
User can more meet the demand of user when carrying out intelligent recommendation.
Intelligent recommendation method provided in an embodiment of the present invention can be applied to more scene, to be applied to online game information
As a example by function of browse, with reference to Fig. 3, it is a kind of intelligence for being applied to online game information browing function provided in an embodiment of the present invention
The signaling interaction diagram of recommendation method.Methods described includes：
S301：The navigation patterns data that server collects user from online game information browing client, bag are collected in behavior
Click behavioral data is included, duration data is browsed, is browsed range data.
S302：The behavior is collected server and collects the user in the online game client from network game client
The behavioral data at end, including the map information residing for the user, people information that the user has, weapon information
Deng.
S303：With reference to the navigation patterns data and the behavioral data in the interested third party application, it is described
User generates label and scoring.
S304：The user is sent to user tag storehouse with the corresponding relation of the label, and is stored in the user
In tag library.
S305：When user opens online game information browing client, triggering intelligent recommendation operation is taken to intelligent recommendation
Business device sends intelligent recommendation request.
S306：The intelligent recommendation server obtains the corresponding label of the user from the user tag storehouse and comments
Point.
S307：The intelligent recommendation server obtains the label correspondence from information storehouse according to the label and scoring
Information.
S308：The information is sequentially issued to the net according to the scoring of each label by the intelligent recommendation server
Network game information browsing client, so that user browses.
S309：When the user is browsed to the information for pushing, the behavior is collected server and collects the user
Navigation patterns data to the information, including click behavioral data, browse duration data, browse range data.
S310：Navigation patterns data of the server according to the user to the information, adjustment storage are collected in the behavior
The scoring of label described in the user tag storehouse.
The intelligent recommendation method for being applied to online game information browing function provided in an embodiment of the present invention, is based not only on use
The navigation patterns at family realize intelligent recommendation, also in relation with behavior of the user in online game.So, what the embodiment of the present invention was supplied
The intelligent recommendation method for being applied to online game information browing function can improve the effect of intelligent recommendation.
The embodiment of the present invention additionally provides a kind of intelligent recommendation device, with reference to Fig. 4, is one kind provided in an embodiment of the present invention
Intelligent recommendation apparatus structure schematic diagram, described device include：
First collection module 401, for collecting the navigation patterns data of user, and the row in interested third party application
For data；
Generation module 402, for reference to the navigation patterns data and the behavior in the interested third party application
Data, are that the user generates label；
Memory module 403, for the user is stored in user tag storehouse with the corresponding relation of the label；
Acquisition module 404, for when user's triggering information browing is operated, obtaining the use from the user tag storehouse
The corresponding label in family；
Pushing module 405, for pushing information according to the label for the user.
In order to further improve the effect of intelligent recommendation, the embodiment of the present invention additionally provides feedback mechanism, accordingly, described
Device also includes：
Determining module, for reference to the navigation patterns data and the behavior number in the interested third party application
According to it, during the user generates label, is that the label determines weighted value to be, the weighted value is used for determining the label
The push order of corresponding information；
Second collection module, for when the user is browsed to the information for pushing, collecting the user to described
The navigation patterns data of information；
Adjusting module, for the navigation patterns data according to the user to the information, adjusts the weight of the label
Value.
Specifically, the navigation patterns data include clicking on behavioral data, browse duration data, browse range data.
In practical application, the interested third party application includes online game application, in the interested third party application
Behavioral data includes the map information residing for the user, people information that the user has, weapon information.
It is a kind of preferred embodiment in, the generation module, including：
Submodule is set, for being respectively the navigation patterns data and the behavior in the interested third party application
Data arrange weighted value；
Submodule is generated, for according to the navigation patterns data and the behavior number in the interested third party application
According to, and the weighted value is combined, it is that the user generates label.
Intelligent recommendation device provided in an embodiment of the present invention can realize following functions：Collect the navigation patterns number of user
According to, and the behavioral data in interested third party application.With reference to the navigation patterns data and in the interested third party
Behavioral data using in, is that the user generates label, and the user is stored in use with the corresponding relation of the label
In the tag library of family.When user's triggering information browing is operated, the corresponding label of the user is obtained from the user tag storehouse,
And information is pushed for the user according to the label.The embodiment of the present invention can be carried out for user based on various behaviors of user
Intelligent recommendation, improves the effect of intelligent recommendation.
Accordingly, the embodiment of the present invention also provides a kind of computer, shown in Figure 5, can include：
Processor 501, memorizer 502, input equipment 503 and output device 504.Server and intelligent recommendation are collected in behavior
The quantity of the processor 501 in server can be with one or more, in Fig. 5 by taking a processor as an example.In some of the invention
In embodiment, processor 501, memorizer 502, input equipment 503 and output device 504 can pass through bus or alternate manner connects
Connect, wherein, in Fig. 5 as a example by being connected by bus.
Memorizer 502 can be used to store software program and module, and processor 501 is stored in memorizer 502 by operation
Software program and module, so as to process performing collects various function application and the number of server and intelligent recommendation server
According to process.Memorizer 502 can mainly include storing program area and storage data field, and wherein, storing program area can store operation system
Application program needed for system, at least one function etc..Additionally, memorizer 502 can include high-speed random access memory, may be used also
With including nonvolatile memory, for example, at least one disk memory, flush memory device or other volatile solid-states
Part.Input equipment 503 can be used for the numeral of receives input or character information, and generation collects server with behavior and intelligence is pushed away
Recommend user's setting and the key signals input that function control is relevant of server.
Specifically in the present embodiment, processor 501 can be according to following instruction, by one or more application program
The corresponding executable file of process be loaded in memorizer 502, and be stored in memorizer 502 to run by processor 501
Application program, so as to realize various functions：
Collect the navigation patterns data of user, and the behavioral data in interested third party application；
With reference to the navigation patterns data and the behavioral data in the interested third party application, it is user's life
Into label；The user is stored in user tag storehouse with the corresponding relation of the label；
When user's triggering information browing is operated, the corresponding label of the user is obtained from the user tag storehouse, and
It is that the user pushes information according to the label.
For device embodiment, as which corresponds essentially to embodiment of the method, so related part is referring to method reality
Apply the part explanation of example.Device embodiment described above is only schematic, wherein described as separating component
The unit of explanation can be or may not be physically separate, as the part that unit shows can be or can also
It is not physical location, you can local to be located at one, or can also be distributed on multiple NEs.Can be according to reality
Need to select some or all of module therein to realize the purpose of this embodiment scheme.Those of ordinary skill in the art are not
In the case of paying creative work, you can to understand and implement.
It should be noted that herein, such as first and second or the like relational terms are used merely to a reality
Body or operation are made a distinction with another entity or operation, and are not necessarily required or implied these entities or deposit between operating
In any this actual relation or order.And, term " including ", "comprising" or its any other variant are intended to
Nonexcludability is included, so that a series of process, method, article or equipment including key elements not only will including those
Element, but also including other key elements being not expressly set out, or also include for this process, method, article or equipment
Intrinsic key element.In the absence of more restrictions, the key element for being limited by sentence "including a ...", it is not excluded that
Also there is other identical element in process, method, article or equipment including the key element.
A kind of intelligent recommendation method and device for being provided to the embodiment of the present invention above is described in detail, herein
Apply specific case to be set forth principle of the invention and embodiment, the explanation of above example is only intended to help
Understand the method for the present invention and its core concept；Simultaneously for one of ordinary skill in the art, according to the thought of the present invention,
Will change in specific embodiments and applications, in sum, this specification content is should not be construed as to this
The restriction of invention.
Claims (10)
1. a kind of intelligent recommendation method, it is characterised in that methods described includes：
Collect the navigation patterns data of user, and the behavioral data in interested third party application；
With reference to the navigation patterns data and the behavioral data in the interested third party application, it is that the user generates mark
Sign；
The user is stored in user tag storehouse with the corresponding relation of the label；
When user's triggering information browing is operated, the corresponding label of the user is obtained from the user tag storehouse, and according to
The label is that the user pushes information.
2. intelligent recommendation method according to claim 1, it is characterised in that methods described also includes：
With reference to the navigation patterns data and the behavioral data in the interested third party application, it is being that the user generates
During label, it is that the label determines weighted value, the weighted value is used for determining the push of the corresponding information of the label
Sequentially；
When the user is browsed to the information for pushing, navigation patterns data of the user to the information are collected；
According to navigation patterns data of the user to the information, the weighted value of the label is adjusted.
3. intelligent recommendation method according to claim 1, it is characterised in that the navigation patterns data include click behavior
Data, browse duration data, browse range data.
4. intelligent recommendation method according to claim 1, it is characterised in that the interested third party application includes that network is swum
Play application, the behavioral data in the interested third party application include the map information residing for the user, the user
The people information that has, weapon information.
5. intelligent recommendation method according to claim 1, it is characterised in that navigation patterns data described in the combination and
Behavioral data in the interested third party application, is that the user generates label, including：
Respectively described navigation patterns data and the behavioral data in the interested third party application arrange weighted value；
According to the navigation patterns data and the behavioral data in the interested third party application, and combine the weight
Value, is that the user generates label.
6. a kind of intelligent recommendation device, it is characterised in that described device includes：
First collection module, for collecting the navigation patterns data of user, and the behavioral data in interested third party application；
Generation module, for reference to the navigation patterns data and the behavioral data in the interested third party application, being
The user generates label；
Memory module, for the user is stored in user tag storehouse with the corresponding relation of the label；
Acquisition module, for when user's triggering information browing is operated, obtaining user's correspondence from the user tag storehouse
Label；
Pushing module, for pushing information according to the label for the user.
7. intelligent recommendation device according to claim 6, it is characterised in that described device also includes：
Determining module, for reference to the navigation patterns data and the behavioral data in the interested third party application,
During label is generated for the user, it is that the label determines weighted value, the weighted value is used for determining the label pair
The push order of the information answered；
Second collection module, for when the user is browsed to the information for pushing, collecting the user to the information
Navigation patterns data；
Adjusting module, for the navigation patterns data according to the user to the information, adjusts the weighted value of the label.
8. intelligent recommendation device according to claim 6, it is characterised in that the navigation patterns data include click behavior
Data, browse duration data, browse range data.
9. intelligent recommendation device according to claim 6, it is characterised in that the interested third party application includes that network is swum
Play application, the behavioral data in the interested third party application include the map information residing for the user, the user
The people information that has, weapon information.
10. intelligent recommendation device according to claim 6, it is characterised in that the generation module, including：
Submodule is set, for being respectively the navigation patterns data and the behavioral data in the interested third party application
Weighted value is set；
Submodule is generated, for according to the navigation patterns data and the behavioral data in the interested third party application,
And the weighted value is combined, it is that the user generates label.
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| CN108769126A (en) * | 2018-04-28 | 2018-11-06 | 努比亚技术有限公司 | Using recommendation method, mobile terminal and computer readable storage medium |
| CN109255076A (en) * | 2018-09-11 | 2019-01-22 | 广东布田电子商务有限公司 | A kind of data push method and system based on user tag system |
| CN109842688A (en) * | 2019-03-07 | 2019-06-04 | 北京达佳互联信息技术有限公司 | A kind of content recommendation method, device, electronic equipment and storage medium |
| CN110237536A (en) * | 2019-06-03 | 2019-09-17 | 北京金山安全软件有限公司 | Personalized game service providing method and device, electronic equipment and storage medium |
| CN112000820A (en) * | 2020-08-10 | 2020-11-27 | 海信电子科技(武汉)有限公司 | Media asset recommendation method and display device |
| CN114265777A (en) * | 2021-12-23 | 2022-04-01 | 北京百度网讯科技有限公司 | Application program testing method and device, electronic equipment and storage medium |
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