CN103618774A - Resource recommending method, device and system based on network behaviors - Google Patents
Resource recommending method, device and system based on network behaviors Download PDFInfo
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Abstract
The invention provides a resource recommending method, device and system based on network behaviors. The method comprises the steps of recording the network behaviors of a client side according to a recommended network resource, iteration is conducted according to the correlation between the recommended network resource and the network resource which conducts the network behaviors to obtain a potential recommended network resource and the transforming rate of the potential recommended network resource, and generating a new recommending list of recommended network resources and sending the new recommending list to the client side according to the recommended network resource, the transforming rate of the network resource conducting the network behaviors, the potential recommended network resource and the transforming rate of the potential recommended network resource. According to the resource recommending method, device and system based on the network behaviors, the network resource using conditions of the client side are taken as feedback to obtain the new recommending list, and then more accurate network resource recommendation is provided for a user.
Description
Technical field
The present invention relates to network technology, particularly a kind of resource recommendation method of behavior Network Based and device, system.
Background technology
Along with the development of network technology, people have more and more browsed or downloaded resources in network.Internet resources are day by day huge, user initiatively searches for and finds needs or interested Internet resources is major ways that user obtains Internet resources, but the time that this mode spends is a lot, to user aspect the ability of search, also require very high, sometimes can the expensive time and the result of searching for is also undesirable.In order to provide sooner online more easily to experience to user, there is network resource recommended technology, according to the conventional property of various network resources or the list of versatility generating recommendations for user.And the less user's of utilization of network resource recommended technology network behavior feeds back.
Summary of the invention
In view of the above problems, proposed the present invention to provide a kind of resource recommendation method of behavior Network Based and device, system, can carry out more accurately network resource recommended.
The resource recommendation method that the invention provides a kind of behavior Network Based, the method comprises:
Record the network behavior that client is carried out according to recommendation network resource, obtain data record;
Extract described data record, the sign of recommendation network resource, the sign of Internet resources of having carried out described network behavior and the conversion ratio that has carried out the Internet resources of described network behavior generate are extracted to record;
According to described recommendation network resource and described in the correlation of having carried out between the Internet resources of described network behavior carry out iteration, obtain the conversion ratio of potential recommendation network resource and described potential recommendation network resource;
According to described recommendation network resource, the conversion ratio that has carried out the Internet resources of described network behavior, potential recommendation network resource and the conversion ratio of described potential recommendation network resource, generate the new recommendation list of described recommendation network resource and send to described client.
Wherein, describedly record the network behavior that client is carried out according to Internet resources, obtain data record and comprise:
The daily record of obtaining described client downloads and/or browsing by result collection system Scribe;
And/or the user installation record and/or the user that record client browse record.
Wherein, the conversion ratio that has carried out the Internet resources of described network behavior described in is to be downloaded the download time of Internet resources divided by showing number of times; And/or, described in carried out number of visits that the conversion ratio of the Internet resources of described network behavior is viewed Internet resources divided by showing number of times.
Wherein, when described recommendation network resource is first network resource, when the Internet resources that carried out described network behavior are second network resource, according to described recommendation network resource and described in the correlation of having carried out between the Internet resources of described network behavior carry out iteration, the conversion ratio that obtains potential recommendation network resource and described potential recommendation network resource comprises:
Described first network resource is directly related with described second network resource; Through an iteration, obtaining described potential recommendation network resource is described second network resource, and the conversion ratio of described potential recommendation network resource is that the conversion ratio of described second network resource is divided by specifying numerical value.
Wherein, when described recommendation network resource is first network resource, the Internet resources that carried out described network behavior are second network resource; And work as described recommendation network resource, it is second network resource, when the Internet resources that carried out described network behavior are the 3rd Internet resources, according to described recommendation network resource and described in the correlation of having carried out between the Internet resources of described network behavior carry out iteration, the conversion ratio that obtains potential recommendation network resource and described potential recommendation network resource comprises:
Described first network resource and described the 3rd Internet resources indirect correlation; Through second iteration, obtaining described potential recommendation network resource is described the 3rd Internet resources, and the conversion ratio of described potential recommendation network resource is that the conversion ratio of described the 3rd Internet resources is specified numerical value divided by two times.
The present invention also provides a kind of device of resource recommendation of behavior Network Based, and this device comprises:
Data center, the network behavior carrying out according to recommendation network resource for recording client, obtains data record;
Recommended engine, for extracting described data record, generate to extract record by the sign of recommendation network resource, the sign of Internet resources of having carried out described network behavior and the conversion ratio that has carried out the Internet resources of described network behavior; According to described recommendation network resource and described in the correlation of having carried out between the Internet resources of described network behavior carry out iteration, obtain the conversion ratio of potential recommendation network resource and described potential recommendation network resource; According to the conversion ratio of described recommendation network resource, the conversion ratio that has carried out the Internet resources of described network behavior, potential recommendation network resource and described potential recommendation network resource, generate the new recommendation list of described recommendation network resource;
Recommending data interface, sends to described client by described new recommendation list.
Wherein, described data center comprises:
Recommending data storehouse, for the daily record of being obtained described client downloads and/or being browsed by result collection system Scribe;
And/or,
Customer data base, browses record for recording user installation record and/or the user of client.
The present invention also provides a kind of resource recommendation system device of behavior Network Based, and this system comprises:
Recommendation server, described server comprises above-mentioned arbitrary described device;
Client, for showing recommendation list and new recommendation list.
The beneficial effect that the present invention brings is as follows:
According to recommendation network resource and the correlation of having carried out between the Internet resources of network behavior, carry out iteration, obtain the conversion ratio of potential recommendation network resource and potential recommendation network resource, thereby using client to the behaviour in service of Internet resources as feedback, obtain new recommendation list, to user, provide network resource recommended more accurately.
Above-mentioned explanation is only the general introduction of technical solution of the present invention, in order to better understand technological means of the present invention, and can be implemented according to the content of specification, and for above and other objects of the present invention, feature and advantage can be become apparent, below especially exemplified by the specific embodiment of the present invention.
Accompanying drawing explanation
By reading below detailed description of the preferred embodiment, various other advantage and benefits will become cheer and bright for those of ordinary skills.Accompanying drawing is only for the object of preferred implementation is shown, and do not think limitation of the present invention.And in whole accompanying drawing, by identical reference symbol, represent identical parts.In the accompanying drawings:
Fig. 1 is the schematic flow sheet of a kind of resource recommendation method of behavior Network Based in the embodiment of the present invention one;
Fig. 2 is the schematic flow sheet of a kind of resource recommendation method of behavior Network Based in the embodiment of the present invention two;
Fig. 3 is the schematic diagram of the application scenarios one of a kind of resource recommendation method of behavior Network Based in the embodiment of the present invention two;
Fig. 4 is the schematic diagram of the application scenarios two of a kind of resource recommendation method of behavior Network Based in the embodiment of the present invention two;
Fig. 5 is the schematic diagram of the application scenarios three of a kind of resource recommendation method of behavior Network Based in the embodiment of the present invention two;
Fig. 6 is the structural representation of a kind of device of resource recommendation of behavior Network Based in the embodiment of the present invention three.
Embodiment
Exemplary embodiment of the present disclosure is described below with reference to accompanying drawings in more detail.Although shown exemplary embodiment of the present disclosure in accompanying drawing, yet should be appreciated that and can realize the disclosure and the embodiment that should do not set forth limits here with various forms.On the contrary, it is in order more thoroughly to understand the disclosure that these embodiment are provided, and can by the scope of the present disclosure complete convey to those skilled in the art.
Below in conjunction with the drawings and specific embodiments, the present invention is further detailed explanation.
In embodiments of the present invention, computing equipment includes but not limited to that client, server etc. are the smart machines with operating system, as desktop computer, and notebook computer etc.Computing equipment can wired mode interconnection network, also can wireless mode interconnection network, and the network connecting can be internet, can be also local area network (LAN).Take wireless mode interconnection network can be as passing through the built-in wireless network card of computing equipment or passing through USB wireless network card.Described wireless network card is set to share after the hotspot of the network that described computing equipment connects, access the mobile terminal such as mobile phone, PAD of this hotspot and just can access the network that this computing equipment connects by this wireless network card, use the bandwidth of this computing equipment connected network, and do not need to spend extra flow rate.The process that concrete wireless network card is set to hotspot refers to follow-up Fig. 2 and associated description.
Refer to Fig. 1, embodiment mono-, a kind of resource recommendation method of behavior Network Based, and the method comprises:
S110 records the network behavior that client is carried out according to recommendation network resource, obtains data record.
In the present embodiment, network behavior includes but not limited to download and/or browse.
In the present embodiment, data include but not limited to that user installation record, the user of the daily record of client downloads, the daily record of browsing, client browse the attribute data that records and/or obtain Internet resources.Wherein, the attribute data of described Internet resources comprises: label (TAG), developer, classification and/or the owner.
For example, for the service end in application shop, can store the user history log of user while using mobile application shop, text formatting storage user history log; User's history log comprises the data of the mobile application that user accessed in mobile application shop, and the mobile application that user accessed comprises the mobile application that user checks or downloads; The data of the mobile application that wherein, user accessed in mobile application shop comprise sign (packageID) and the access time of user ID (UID), mobile application.
In the present embodiment, the mode that obtains data record can include but not limited to:
The daily record of obtaining described client downloads and/or browsing by result collection system Scribe;
And/or the user installation record and/or the user that record client browse record.
And/or, the attribute data of the Internet resources in the service end database at DUMP Internet resources place.
In an embodiment, client includes but not limited to PC and/or mobile terminal.
In an embodiment, Internet resources at least comprise one of APP, music, game, novel, video and picture.
In order to improve the fail safe of data, in the present embodiment, described data record is encrypted by irreversible encryption algorithm.
S120 extracts described data record, and the sign of recommendation network resource, the sign of Internet resources of having carried out described network behavior and the conversion ratio that has carried out the Internet resources of described network behavior generate are extracted to record.
In the present embodiment, conversion ratio is to be downloaded the download time of Internet resources divided by showing number of times; And/or the number of visits of viewed Internet resources is divided by showing number of times.
For ease of consulting, in the present embodiment, extracting record can be with behavior unit, every behavior three row, and first classifies the sign of recommendation network resource as, second classifies the sign of the Internet resources that carried out described network behavior as, and the 3rd classifies the conversion ratio of the Internet resources that carried out described network behavior as.
S130 according to described recommendation network resource and described in the correlation of having carried out between the Internet resources of described network behavior carry out iteration, obtain the conversion ratio of potential recommendation network resource and described potential recommendation network resource.
In the present embodiment, optionally, when described recommendation network resource is first network resource, when the Internet resources that carried out described network behavior are second network resource, according to described recommendation network resource and described in the correlation of having carried out between the Internet resources of described network behavior carry out iteration, the conversion ratio that obtains potential recommendation network resource and described potential recommendation network resource comprises:
Described first network resource is directly related with described second network resource; Through an iteration, obtaining described potential recommendation network resource is described second network resource, and the conversion ratio of described potential recommendation network resource is that the conversion ratio of described second network resource is divided by specifying numerical value.Optionally, in the present embodiment, specifying numerical value is 2.
For example, first network resource is APP1, second network resource is APP2, by APP1, browsed APP2, through an iteration, obtaining browsing APP1 by APP2 is potential browsing, and the number of visits that the conversion ratio of APP2 is APP2 is divided by the displaying number of times of APP2, conversion ratio/2 that the so potential transfer ratio of browsing is APP2.
Again for example, first network resource is APP1, second network resource is APP2, by APP1, browsed APP2, through an iteration, obtaining downloading APP1 by APP2 is potential download, and the number of visits that the conversion ratio of APP2 is APP2 is divided by the displaying number of times of APP2, conversion ratio/2 that the transfer ratio of so potential download is APP2.
In the present embodiment, optional, when described recommendation network resource is first network resource, the Internet resources that carried out described network behavior are second network resource; And work as described recommendation network resource, it is second network resource, when the Internet resources that carried out described network behavior are the 3rd Internet resources, according to described recommendation network resource and described in the correlation of having carried out between the Internet resources of described network behavior carry out iteration, the conversion ratio that obtains potential recommendation network resource and described potential recommendation network resource comprises:
Described first network resource and described the 3rd Internet resources indirect correlation; Through second iteration, obtaining described potential recommendation network resource is described the 3rd Internet resources, and the conversion ratio of described potential recommendation network resource is that the conversion ratio of described the 3rd Internet resources is specified numerical value divided by two times.
For example, first network resource is APP1, and second network resource is APP2, and the 3rd Internet resources are APP3, by APP1, downloaded APP2, by APP2, downloaded APP3, so, APP1 and APP3 are indirect correlation, through second iteration, obtaining downloading APP3 by APP1 is potential download, and the number of visits that the conversion ratio of APP3 is APP3 is divided by the displaying number of times of APP3, conversion ratio/4 that the transfer ratio of so potential download is APP3.
Again for example, first network resource is APP1, and second network resource is APP2, and the 3rd Internet resources are APP3, by APP1, downloaded APP2, by APP2, browsed APP3, so, APP1 and APP3 are indirect correlation, through second iteration, obtaining downloading/browse APP3 by APP1 is potential download, and the number of visits that the conversion ratio of APP3 is APP3 is divided by the displaying number of times of APP3, conversion ratio/4 that the transfer ratio of so potential download/browse is APP3.
S140 generates the new recommendation list of described recommendation network resource and sends to described client according to described recommendation network resource, the conversion ratio that has carried out the Internet resources of described network behavior, potential recommendation network resource and the conversion ratio of described potential recommendation network resource.
In the present embodiment, the new recommendation list that generates described recommendation network resource according to the conversion ratio of described recommendation network resource, the conversion ratio that has carried out the Internet resources of described network behavior, potential recommendation network resource and described potential recommendation network resource comprises:
The described conversion ratio of Internet resources and the conversion ratio of described potential recommendation network resource that has carried out described network behavior sorted from big to small, generate the new recommendation list of described recommendation network resource.
After iteration, the length of new recommendation list likely can be less than the length of recommendation list, now, the recommendation network resource obtaining by other algorithms is supplemented until the length of described new recommendation list equals the length of described recommendation list.
In concrete application, can adopt different algorithms, can include but not limited to collaborative filtering (ITEM-BASED CF) based on article and/or collaborative filtering based on user (USER-BASED CF) etc., according to the rank of the transfer ratio obtaining after various algorithm application, the preceding algorithm of regular or irregular employing rank, recommendation network resource is carried out to iteration, and the result obtaining is supplemented in new recommendation list.
The concrete application of technique scheme, can comprise the steps:
A) first 10 days of server timing extraction every day get daily record ready, this gets daily record ready is the download behavior bringing by commending system.What extract gets daily record ready with behavior unit, every behavior three row, and first classifies the appid of recommendation as, and second classifies the appid of recommended download as, and the 3rd classifies conversion ratio as, and download time is divided by showing number of times.
B) by the daily record of getting ready extracting, carry out iteration, to produce more possible download, alternative manner has two kinds:
1. by app1, download the user of app2, also likely by app2, downloaded app1;
2. by app1, download app2, by app2, downloaded app3, by app1, also likely downloaded app3 so.Often carry out iteration one time, conversion ratio, divided by a fixing numerical value, is 2.0 at present.
C), by the iteration of B process, can produce more many potential download behaviors.Potential download behavior adds that the download having had just can be used as the recommendation that metadata carries out downloading based on user behavior.
D) metadata producing by C process can be utilized the app of first row when recommending, and recommends the app of secondary series, and the order of recommendation is arranged by backward with the size of conversion ratio.This algorithm may cause recommendation list length inadequate, now can adopt the result of other proposed algorithms to select from front to back to supplement according to the needed length of recommendation list, to meet recommendation list, shows needed length.
Due to according to user's feedback, increased potential recommendation, the download conversion ratio of the Internet resources that are gets a promotion.
Embodiment bis-, a kind of resource recommendation method of behavior Network Based, in the present embodiment, client comprises PC end and mobile terminal, mobile terminal in the present embodiment is mobile phone, the applied environment of the technical program be the web browser of PC end recommendation details page, PC end I mobile phone display page and/or the recommendation details page of mobile phone.
The technical scheme of the present embodiment comprises the steps:
S210 collects the data of the network behavior that user carries out according to recommendation network resource from client, the present embodiment is applied in following several prods: the recommendation details page of the web browser of PC end, PC end I mobile phone display page and the recommendation details page of mobile phone.
The data that S220 collects are stored in data Layer, can classify and be kept in customer data base, recommending data storehouse and APP database.Wherein, subscriber database stores includes but not limited to that user installation record and the user of client browse record.In APP database, store the attribute data of APP.Recommending data library storage includes but not limited to the daily record of client downloads and the daily record of browsing; Recommending data storehouse can also include but not limited to the title of a plurality of mobile application and the download link of a plurality of mobile application etc.Particularly, its descriptor can also be revised by name service provider for mobile application, descriptor can be so that be used the user of mobile application can clearly identify that in mobile set of applications, each moves the main contents of application, facilitates user to download, install and the operation such as unloading.
The data of S230 recommended engine extracted data layer storage, the sign of recommendation network resource, the sign of Internet resources of having carried out described network behavior and the conversion ratio that has carried out the Internet resources of described network behavior generate are extracted to record, and according to described recommendation network resource and described in the correlation of having carried out between the Internet resources of described network behavior carry out iteration, obtain the conversion ratio of potential recommendation network resource and described potential recommendation network resource; Afterwards, according to the conversion ratio of described recommendation network resource, the conversion ratio that has carried out the Internet resources of described network behavior, potential recommendation network resource and described potential recommendation network resource, generate the new recommendation list of described recommendation network resource.
In specific implementation, can adopt and recommend real-time computing engines and/or recommendation calculated off-line engine two cover recommended engines to process, thereby the speed of data processing and efficiency are taken into account.
S240 pushes the new recommendation list obtaining by recommending data interface, in order to improve pushing efficiency, can be according to the different interface of the different employings of the receiving terminal of new recommendation list, in the present embodiment, the receiving terminal of interface 1 correspondence is the recommendation details page of the web browser of PC end, the receiving terminal of interface 2 correspondences is my mobile phone display page of PC end, the recommendation details page that the receiving terminal of interface 3 correspondences is mobile phone.
S250 is pushed to corresponding product by different service end front end interfaces by new recommendation list respectively, in the present embodiment, by intf interface by new recommendation list be pushed to the web browser of PC end recommendation details page, by third assistant's interface by new recommendation list be pushed to PC end I mobile phone display page and by mobile phone terminal interface, new recommendation list is pushed to the recommendation details page of mobile phone.
While pushing product by service end front end, pc or mobile phone can obtain the web page contents of current demonstration on described computing equipment from corresponding server.
In order to meet user's demand, save data traffic, the selected target that will transmit in webpage, for example, selectes a few moneys game in advance, or certain wallpaper etc., for selected target, can carry out mark, thereby when the web page contents of current demonstration is resolved, can detect in this webpage, whether there is selected target (target of tape label), if there is selected target, obtain this selected content.If not selected any target in webpage detected, now can think that the content in whole webpage is all selected target, thereby transmit the content in whole webpage.
Can be according to selected target in the embodiment of the present invention, obtain one or more in following descriptor, wherein, described descriptor includes but not limited to the title of described target, the size of data of the memory address of described target, described target and the thumbnail of described target.Wherein, described title is the title of selected target, as game name, web page title etc.Described memory address is the memory address of the related data of selected target, and if selected target is game, described memory address can be the download address of single-play game, or the reference address of online game etc.Described size of data is the data volume of the related data of selected target, and if selected target is single-play game, described size of data can be the data volume of the installation procedure of this single-play game, as 2M; And for example selected target is wallpaper, and described size of data is exactly the size of this wallpaper.Described thumbnail is the picture that can show the content of selected target, while being webpage as selected target, described thumbnail can be the Logo of this website, webpage place, and for example, selected target is game, and described thumbnail can be the placard picture of this game etc.
Transmitting procedure data acquisition can be configured to Json form by initialize format, and the data of initialize format can be the character string of Json form.
Also comprise concrete application, as " Dungeon is with brave ... ", " lamb general mobilization " and " forgetting celestial being " etc.Wherein, " Dungeon is with brave ... " full name Shi“ DNF official legal ", because the position in webpage is limited, therefore only shown division name.
Suppose, now selected target Shi“ DNF official is legal ", computing equipment can obtain the character string of the descriptor formation Json form of " DNF official is legal ".Wherein, a kind of exemplary form of the character string of Json form is as follows:
[{ " attach ": [{ " Market_name ": " ", " apkid ": " com.Nexon.DunfightENGF360 ", " filedispname ": " the formal version 1.01 of DNF official ", " filename ": " the formal version 1.01.apk of DNF official ", " filesize ": " 28899475 ", " filethumb ": "
http:// p3.qhimg.com/t01 617c9165b3dae3eb.png"; " filetype ": " app "; " fileurl ": " http://shouji.360safe.com/360sj/adm/apk/20121215/com.Nexon.Dunf ightENGF360_2_194130.apk "; " format ": " apk "; " mid ": " 12fcd727fc624ed180de17e94ff72c67ca1089050c376ba8a499618b ea589322 ", " msgsource ": " mobile phone assistant
In the character string of above-mentioned Json form, identify Liao“ DNF official legal " descriptor, as memory address (fileurl), and for example size of data (filesize), also comprises the type (filetype) of " DNF official is legal " etc.
Computing equipment sends to server by the web page contents of current demonstration.
Computing equipment can send to server by the character string of the above Json form.
Server is stored the web page contents of described current demonstration, and spanned file obtains message.
Server is stored by the character string of this Json form and spanned file obtains message, wherein, and the memory address that comprises the character string of this Json form in server in file acquisition message.
Server sends described file acquisition message to mobile device.
Mobile device obtains the web page contents of current demonstration on described computing equipment from server.
Mobile device can conduct interviews to the memory address of the character string of this Json form in server, thereby obtains the character string of this Json form.
Mobile device is resolved and shows the web page contents of current demonstration on described computing equipment.
Mobile device is resolved the character string of Json form, and is shown on the screen of mobile device.
As got at mobile device after the character string of Json form, when it is resolved, transforms generation demonstration data, can show described chained address, thereby by this chained address, can obtain the related data of described selected target.When descriptors such as described chained address and thumbnail or titles, carry out associatedly, can trigger described chained address by clicking thumbnail or title, obtain the related data of described selected target.
Refer to Fig. 3, for the schematic diagram of the recommendation details page of the web browser of the one PC end of application scenarios in the present embodiment, wherein, guess that you like a hurdle for the recommendation list for 360 mobile phone bodyguards.
Refer to Fig. 4, for my schematic diagram of mobile phone display page of the two PC ends of application scenarios in the present embodiment, wherein, guess that you may also like a hurdle for the recommendation list for 360 address lists.
Referring to Fig. 5, is the schematic diagram of the recommendation details page of three mobile phones of application scenarios in the present embodiment, wherein, guesses that you like a hurdle for the recommendation list for Sina's microblogging cell-phone customer terminal.
Embodiment tri-, refer to Fig. 6, a kind of device of resource recommendation of behavior Network Based, and this device comprises:
Recommending data interface 630, sends to described client by described new recommendation list.
Wherein, described data center comprises:
Recommending data storehouse, for the daily record of being obtained described client downloads and/or being browsed by result collection system Scribe;
And/or,
Customer data base, browses record for recording user installation record and/or the user of client.
Wherein, described data center also comprises:
APP database, for obtaining corresponding attribute data from the service end of described APP.
The present invention also provides a kind of resource recommendation system device of behavior Network Based, and this system comprises:
Recommendation server, described server comprises above-mentioned arbitrary described device;
Client, for showing recommendation list and new recommendation list.
Those skilled in the art should understand, the application's embodiment can be provided as method, system or computer program.Therefore, the application can adopt complete hardware implementation example, implement software example or in conjunction with the form of the embodiment of software and hardware aspect completely.And the application can adopt the form that wherein includes the upper computer program of implementing of computer-usable storage medium (including but not limited to magnetic disc store, CD-ROM, optical memory etc.) of computer usable program code one or more.
The application is with reference to describing according to flow chart and/or the block diagram of the method for the embodiment of the present application, equipment (system) and computer program.Should understand can be in computer program instructions realization flow figure and/or block diagram each flow process and/or the flow process in square frame and flow chart and/or block diagram and/or the combination of square frame.Can provide these computer program instructions to the processor of all-purpose computer, special-purpose computer, Embedded Processor or other programmable data processing device to produce a machine, the instruction of carrying out by the processor of computer or other programmable data processing device is produced for realizing the device in the function of flow process of flow chart or a plurality of flow process and/or square frame of block diagram or a plurality of square frame appointments.
These computer program instructions also can be stored in energy vectoring computer or the computer-readable memory of other programmable data processing device with ad hoc fashion work, the instruction that makes to be stored in this computer-readable memory produces the manufacture that comprises command device, and this command device is realized the function of appointment in flow process of flow chart or a plurality of flow process and/or square frame of block diagram or a plurality of square frame.
These computer program instructions also can be loaded in computer or other programmable data processing device, make to carry out sequence of operations step to produce computer implemented processing on computer or other programmable devices, thereby the instruction of carrying out is provided for realizing the step of the function of appointment in flow process of flow chart or a plurality of flow process and/or square frame of block diagram or a plurality of square frame on computer or other programmable devices.
Although described the application's preferred embodiment, once those skilled in the art obtain the basic creative concept of cicada, can make other change and modification to these embodiment.So claims are intended to all changes and the modification that are interpreted as comprising preferred embodiment and fall into the application's scope.
Obviously, those skilled in the art can carry out various changes and modification and the spirit and scope that do not depart from the application to the application.Like this, if within these of the application are revised and modification belongs to the scope of the application's claim and equivalent technologies thereof, the application is also intended to comprise these changes and modification interior.
Claims (10)
1. a resource recommendation method for behavior Network Based, is characterized in that, the method comprises:
Record the network behavior that client is carried out according to recommendation network resource, obtain data record;
Extract described data record, the sign of recommendation network resource, the sign of Internet resources of having carried out described network behavior and the conversion ratio that has carried out the Internet resources of described network behavior generate are extracted to record;
According to described recommendation network resource and described in the correlation of having carried out between the Internet resources of described network behavior carry out iteration, obtain the conversion ratio of potential recommendation network resource and described potential recommendation network resource;
According to described recommendation network resource, the conversion ratio that has carried out the Internet resources of described network behavior, potential recommendation network resource and the conversion ratio of described potential recommendation network resource, generate the new recommendation list of described recommendation network resource and send to described client.
2. method according to claim 1, is characterized in that: described network behavior comprises to be downloaded and/or browses.
3. method according to claim 2, is characterized in that, describedly records the network behavior that client is carried out according to Internet resources, obtains data record and comprises:
The daily record of obtaining described client downloads and/or browsing by result collection system Scribe;
And/or the user installation record and/or the user that record client browse record;
And/or, obtain the attribute data of Internet resources, wherein, the attribute data of described Internet resources comprises: label, developer, classification and/or the owner.
4. method according to claim 2, is characterized in that: described in carried out the Internet resources of described network behavior conversion ratio be to be downloaded the download time of Internet resources divided by showing number of times; And/or, described in carried out number of visits that the conversion ratio of the Internet resources of described network behavior is viewed Internet resources divided by showing number of times.
5. method according to claim 1, it is characterized in that, when described recommendation network resource is first network resource, when the Internet resources that carried out described network behavior are second network resource, according to described recommendation network resource and described in the correlation of having carried out between the Internet resources of described network behavior carry out iteration, the conversion ratio that obtains potential recommendation network resource and described potential recommendation network resource comprises:
Described first network resource is directly related with described second network resource; Through an iteration, obtaining described potential recommendation network resource is described second network resource, and the conversion ratio of described potential recommendation network resource is that the conversion ratio of described second network resource is divided by specifying numerical value;
Or when described recommendation network resource is first network resource, the Internet resources that carried out described network behavior are second network resource; And work as described recommendation network resource, it is second network resource, when the Internet resources that carried out described network behavior are the 3rd Internet resources, according to described recommendation network resource and described in the correlation of having carried out between the Internet resources of described network behavior carry out iteration, the conversion ratio that obtains potential recommendation network resource and described potential recommendation network resource comprises:
Described first network resource and described the 3rd Internet resources indirect correlation; Through second iteration, obtaining described potential recommendation network resource is described the 3rd Internet resources, and the conversion ratio of described potential recommendation network resource is that the conversion ratio of described the 3rd Internet resources is specified numerical value divided by two times.
6. method according to claim 1, is characterized in that, described appointment numerical value is 2.
7. method according to claim 1, it is characterized in that, the new recommendation list that generates described recommendation network resource according to the conversion ratio of described recommendation network resource, the conversion ratio that has carried out the Internet resources of described network behavior, potential recommendation network resource and described potential recommendation network resource comprises:
The described conversion ratio of Internet resources and the conversion ratio of described potential recommendation network resource that has carried out described network behavior sorted from big to small, generate the new recommendation list of described recommendation network resource;
And/or, when the length of described new recommendation list is less than the length of described recommendation list, supplement until the length of described new recommendation list equals the length of described recommendation list.
8. a device for the resource recommendation of behavior Network Based, is characterized in that, this device comprises:
Data center, the network behavior carrying out according to recommendation network resource for recording client, obtains data record;
Recommended engine, for extracting described data record, generate to extract record by the sign of recommendation network resource, the sign of Internet resources of having carried out described network behavior and the conversion ratio that has carried out the Internet resources of described network behavior; According to described recommendation network resource and described in the correlation of having carried out between the Internet resources of described network behavior carry out iteration, obtain the conversion ratio of potential recommendation network resource and described potential recommendation network resource; According to the conversion ratio of described recommendation network resource, the conversion ratio that has carried out the Internet resources of described network behavior, potential recommendation network resource and described potential recommendation network resource, generate the new recommendation list of described recommendation network resource;
Recommending data interface, sends to described client by described new recommendation list.
9. device according to claim 8, is characterized in that, described data center comprises:
Recommending data storehouse, for the daily record of being obtained described client downloads and/or being browsed by result collection system Scribe;
And/or,
Customer data base, browses record for recording user installation record and/or the user of client;
And/or,
APP database, for obtaining corresponding attribute data from the service end of described APP.
10. a resource recommendation system device for behavior Network Based, is characterized in that, this system comprises:
Recommendation server, described server comprises the arbitrary described device of claim 8 or 9;
Client, for showing recommendation list and new recommendation list.
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