CN104601659B - Using recommendation method and system - Google Patents
Using recommendation method and system Download PDFInfo
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- CN104601659B CN104601659B CN201410785047.3A CN201410785047A CN104601659B CN 104601659 B CN104601659 B CN 104601659B CN 201410785047 A CN201410785047 A CN 201410785047A CN 104601659 B CN104601659 B CN 104601659B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/50—Network services
- H04L67/535—Tracking the activity of the user
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/2866—Architectures; Arrangements
- H04L67/30—Profiles
- H04L67/306—User profiles
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/34—Network arrangements or protocols for supporting network services or applications involving the movement of software or configuration parameters
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/50—Network services
- H04L67/55—Push-based network services
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Abstract
Recommend method and system this application discloses one kind application, including：The same specified attribute user of targeted customer is determined, the mounted application of same specified attribute user is determined, first kind candidate application is used as using identified application；The application preferences information of targeted customer is obtained, the preference application of targeted customer is determined according to the application preferences information；For each described preference application, it is determined that the application downloaded using the user that preference application has been downloaded in download system, identified application is applied as Equations of The Second Kind candidate；Selection in being applied with Equations of The Second Kind candidate is applied to meet the application of specified requirements as recommendation application from the first kind candidate；Terminal where triggering the targeted customer downloads the recommendation application automatically.Using the present invention, intended application and the matching degree of targeted customer can be improved, the operating efficiency of user installation intended application is improved.
Description
Technical field
The application is related to computer and internet data processing technology field, more particularly to one kind applies recommendation method and is
System.
Background technology
With intelligent terminal continue to develop and people are to the continuous of application program (APP, referred to as using) demand
The various applications used in increase, terminal enter in the visual field of people at leisure, facilitate the life of people.
In the prior art, substantial amounts of application signs in on the platform of major intelligent terminals, and the quantity of application
It is that very large, newly-increased application is also many.Under normal circumstances, terminal device has no way of understanding these applications, certainly
Download will not be gone to use it.Each application provider is by recommending its new opplication to terminal device using recommendation server or using
The higher application of frequency, and the function of application is introduced, so that terminal device chooses whether to use according to self-demand.
But, at least there is problems with prior art：
Existing application recommends method to be entirely that application provider has been downloaded by application recommendation server according to application
And/or the height for the number of times frequency etc. installed is recommended, or application provider wants the new opplication of distribution and recommends use
Family, and these applications recommended are not often the application required for terminal device, therefore, in the scheme of prior art apply and push away
Recommend less efficient.User is often carried out artificial to obtain the intended application matched with oneself (application oneself needed)
Search, search, check brief introduction, the operation such as on probation, these operations not only occupy the plenty of time of user, cause user to find
The inefficient operation of the intended application matched with own situation, and these operations can largely consume the money of user's intelligent terminal
Source, including cpu resource, storage resource, bandwidth resources etc., cause the waste of resource.
The suggested design of prior art only recommends application, does not help user to download, and user stills need to download manually and installed
After can experience and use, operating efficiency is relatively low.
The content of the invention
In view of this, the main object of the present invention is to provide a kind of application recommendation method and system, to improve intended application
With the matching degree of targeted customer, the operating efficiency of user installation intended application is improved.
The technical proposal of the invention is realized in this way：
One kind application recommendation method, including：
The same specified attribute user of targeted customer is determined, the mounted application of same specified attribute user is determined, with institute
The application of determination is applied as first kind candidate；
The application preferences information of targeted customer is obtained, the preference application of targeted customer is determined according to the application preferences information；
For each described preference application, it is determined that the application downloaded using the user that preference application has been downloaded in download system,
It regard identified application as Equations of The Second Kind candidate application；
Selection in being applied with Equations of The Second Kind candidate is applied to meet the application of specified requirements as recommendation from the first kind candidate
Using；
Terminal where triggering the targeted customer downloads the recommendation application automatically.
One kind application commending system, including：
Attribute recommending module, the same specified attribute user for determining targeted customer, determines the same specified attribute user
Mounted application, first kind candidate application is used as using identified application；
Preference recommending module, the application preferences information for obtaining targeted customer, mesh is determined according to the application preferences information
Mark the preference application of user；For each described preference application, it is determined that using downloaded in download system the preference application
The application that user is downloaded, identified application is applied as Equations of The Second Kind candidate；
Recommending module is selected, meets specified bar with selection in Equations of The Second Kind candidate application for being applied from the first kind candidate
The application of part is used as recommendation application；
Automatic download module, terminal where for triggering the targeted customer downloads the recommendation application automatically.
Compared with prior art, present invention can ensure that the personal attribute of user and all being covered with two dimensions of application preferences
Lid, acquisition is more accurately recommended, that is, the application recommended and the matching degree of targeted customer are more accurate, improve matching degree, mesh
Mark user need not carry out cumbersome searching operation again, improve the operating efficiency that user is found and installation targets are applied.Simultaneously as
Terminal downloads recommended application automatically where the present invention can trigger targeted customer, and user can be mounted directly the application, without
Wait for downloads, therefore improve the operating efficiency of targeted customer's installation targets application.
Brief description of the drawings
Fig. 1 is a kind of schematic flow sheet that method is recommended in application of the present invention；
Fig. 2 is the setting interface schematic diagram of the default mobile phone state for allowing to download automatically；
The setting schematic diagram for the preset mobile phone state that Fig. 3 is downloaded automatically for termination；
Fig. 4 is the schematic diagram that a kind of client homepage triggers recommendation information Entry Interface；
Fig. 5 is a kind of schematic diagram of recommendation information Entry Interface of the present invention；
Fig. 6 show the detail information displaying schematic diagram for recommending application；
Fig. 7 is pop-up schematic diagram when exiting recommendation information Entry Interface；
Fig. 8 is a kind of composition schematic diagram of application commending system of the present invention；
Fig. 9 is another composition schematic diagram of the application commending system.
Embodiment
Below in conjunction with the accompanying drawings and specific embodiment the present invention is further described in more detail.
Fig. 1 is a kind of schematic flow sheet that method is recommended in application of the present invention.As shown in figure 1, the application of the present embodiment
Recommendation method specifically may comprise steps of：
Step 101, the same specified attribute user for determining targeted customer, determine that the same specified attribute user is mounted and answer
With, using it is identified application be used as the first kind candidate application.
The specified attribute is the attribute of preassigned user, such as described specified attribute can include：Position, property
Not, age, and/or occupation etc.；Corresponding, the same specified attribute user is：Its specified attribute is with the targeted customer's
Specified attribute is with the user in the range of a specified attribute.It is same position with specified attribute user for example for position attribution
Properties user, the same position attribution user refers to the user that the position with targeted customer is in together in a geographic range, example
Such as centered on the position of targeted customer, in circle of the radius for k (k can be preset), the user in the circle is exactly mesh
Mark the same position attribution user of user；It is same age properties user, described the same year with specified attribute user again for example for the age
Age properties user refers to the user being in together in a range of age at the age with targeted customer, such as 15~18 years old, 19~23
Year, 24~28 years old etc..By that analogy, the same sex properties user refer to targeted customer sex identical user, it is described
Refer to that the occupation with targeted customer is identical or belongs to user mutually of the same trade with professional properties user.
In a further embodiment, it may further determine that the same specified attribute user refers to recently in step 101
The information of section of fixing time (such as nearly one month) mounted application, first kind candidate application is used as using identified application.
Step 102, the application preferences information for obtaining targeted customer, determine that targeted customer's is inclined according to the application preferences information
Good application；For each described preference application, it is determined that being downloaded using the user that preference application has been downloaded in download system
Application, using it is identified application be used as Equations of The Second Kind candidate apply.
There is no strict sequencing between above-mentioned steps 101 and 102, can also first carry out and step is performed after step 102
101, it can also perform simultaneously.
Step 103, from the first kind candidate apply and Equations of The Second Kind candidate application in selection meet the application of specified requirements
It is used as recommendation application.
Terminal where step 104, the triggering targeted customer downloads the recommendation application automatically.It is specifically automatic to download institute
The installation kit for recommending application is stated, also referred to herein simply as downloads and recommends application.
In the present invention, the step 101 to 103 can be performed by server end, and the step 104 can be by end side
Client executing.
In the present invention, the client typically refer to user mutual end, can specifically pass through special client
(Client) realize, can also be realized web browser (Browser) by way of accessing server, you can with using clear
Look at device/server (B/S) structure, it would however also be possible to employ client/server (C/S) structure, but developed rapidly in the network information
Age, system architecture may also can develop and change, however, being what framework, core concept of the invention and the work(of core
Energy module is identical, and the present position for simply performing the module of concrete function is different.
In an advantageous embodiment, the step 103, specifically includes step 1311 and step 1312：
Step 1311, judge each application in first kind candidate application and Equations of The Second Kind candidate application whether by mesh
Mark user installation, if it is from the first kind candidate apply and Equations of The Second Kind candidate application in delete the targeted customer and installed
Application；And/or, the issuing time that the first kind candidate applies and respectively applied in Equations of The Second Kind candidate application is determined, hair is deleted
The cloth time exceedes the application for the time of specifying；
Step 1312, remaining first kind candidate application and Equations of The Second Kind candidate applied as recommending application.
In another specific embodiment, the step 103 is answered from the first kind candidate using with Equations of The Second Kind candidate
When the application for meeting specified requirements with middle selection is applied as recommendation, this method can further include the He of following steps 1321
Step 1322：
Step 1321, determine that the first kind candidate applies the installation number of users in the same specified attribute user, with
The installation number of users is ranked up to first kind candidate application, and installation number of users is deleted from first kind candidate application and is less than
The application of specified threshold；
Step 1322, the common probability of occurrence that the application in Equations of The Second Kind candidate application is applied with the preference is determined,
Equations of The Second Kind candidate application is ranked up with the common probability of occurrence, deletes described jointly to go out from Equations of The Second Kind candidate application
Existing probability is less than the application of specified threshold.
In a kind of specific preferred embodiment, the step 104 specifically includes following steps 1411~1413：
Terminal where step 1411, the list information for applying the recommendation are sent to the targeted customer,
Terminal where step 1412, the triggering targeted customer judges whether include this terminal in the recommendation list of application
The size of application, downloaded application or the installation kit installed is more than the application of predetermined threshold, if it is, from institute
State the size for recommending to delete application, downloaded application or installation kit that described terminal has been installed in list of application big
In the application of predetermined threshold；
Terminal where step 1413, the triggering targeted customer is downloaded in the recommendation list of application N before sequence automatically
Application, the N be default natural number.
In another specific preferred embodiment, the step 104 can also specifically include：Judge the targeted customer
Place terminal has been downloaded automatically and whether old recommendation application number before the deadline is less than specified quantity, is being determined as
In the case of trigger the targeted customer where terminal download new recommendation application automatically.
Further, in the present embodiment, the terminal where the targeted customer is triggered in the case of being judged to being is certainly
It is dynamic to download new recommendation application, specifically include following steps 1421 and 1422：
Step 1421, terminal where the targeted customer has been downloaded automatically and the old recommendation more than the term of validity should
It is ranked up with according to download time；
Step 1422, delete during described having downloaded automatically and more than the term of validity old recommendation is applied download time most
Application is recommended in early Geju City, and terminal where triggering the targeted customer is downloaded before the new sequence most recommended in application automatically
One new recommend application；Judge whether old recommendation application that is also having downloaded automatically and exceeding the term of validity, if it is
This step is repeated, otherwise terminates this step.
In a further embodiment, the method for the invention is whole where the triggering targeted customer described in step 104
End is downloaded after the recommendation application automatically, can further include：
Step 151, the terminal display recommendation information Entry Interface where the targeted customer, in recommendation information entrance circle
The information for the recommendation application downloaded automatically is shown in face；
Step 152, when receive in the recommendation information Entry Interface it is a certain it is described recommend application browsing instructions when
(icon for being generally click on recommendation application), then show the detail information of recommendation application；Receiving what the recommendation was applied
During installation instruction, terminal where triggering the targeted customer installs the recommendation application；
Step 153, after the recommendation information Entry Interface is exited, deletion browsed but the uninstalled recommendation should
With.
It is discussed in detail separately below in the above method and recommends to apply with the specified attribute selection first kind of targeted customer, and
The specific method of application is recommended with the preference information selection Equations of The Second Kind of targeted customer.
It is described to recommend to apply with the specified attribute selection first kind of targeted customer, it is exactly the personal attribute (position according to user
Put, sex, the age, occupation etc.), calculate user's application interested, pre-download carried out in the case of user's unaware..
For example, in a kind of specific embodiment, it is attached to select to recommend for user using position attribution as the specified attribute
The application that nearly user is using, you can referred to as nearby to play application, mainly include the following steps that (11)~(16)：
(11) customer location is determined.Specifically include：The X place that user often haunts is calculated, is determined with the method for cluster
Longitude and latitude is interval.
(12) nearby users of targeted customer are determined, that is, determine the use in the specified geographic range of targeted customer position
Family, such as typically using targeted customer position as the center of circle, according to specified radius one circle of picture, the user within the scope of the circle, this
These users are referred to as nearby users by place.It is then determined that each nearby users specify mounted application in the period nearest
Information, the list of generation one candidate application, wherein mainly title, mark including each application etc.；Determine that the candidate should
Installation number of users in the nearby users, using the candidate apply installation number of users in the nearby users as
Recommendation degree；The candidate applies the installation number of users in the nearby users to be referred to as：Close positions are playing number of users.For example
Circular can include：List of application is being played in calculate the people of the vicinity in a places of often haunting nearest one week, described
Refer to the application that user has installed playing application, how much be ranked up according in object for appreciation user.
(13) installation number of users in the nearby users is applied as recommendation degree using the candidate, according to the recommendation degree
Candidate's list of application is ranked up.Candidate's application herein is exactly first kind candidate application described above.
(14) its recommendation degree is deleted from candidate's list of application, and less than appointed threshold value, (such as x, x value can be pre-set
Adjustment, such as default value are application 5), i.e., to be filtered out from candidate's list of application and nearby play user's answering less than x people
With.
(15) judge whether each application in candidate's list of application is installed by targeted customer, if it is from institute
State and the mounted application of the targeted customer is deleted in candidate's list of application.
(16) issuing time respectively applied in candidate's list of application is determined, hair is deleted from candidate's list of application
The cloth time exceedes the application for specifying the time (such as 1 month).
For another example in another specific embodiment, it is same to select to recommend for user using gender attribute as specified attribute
The application that sex user is using, mainly includes the following steps that (21)~(26)：
(21) user's sex is determined.It can specifically be determined according to the existing customer attribute information of each user.
(22) the same sex user of targeted customer is determined, determines that the same sex user has pacified in nearest specify in the period
The information of the application of dress, the list of one candidate's application of generation, wherein mainly title, mark including each application etc.；Determine institute
State candidate and apply the installation number of users in the same sex user, the peace in the same sex user is applied with the candidate
Dress number of users is used as recommendation degree；The candidate applies the installation number of users in the same sex user to be referred to as：Exist with sex
Play number of users.
(23) installation number of users in the same sex user is applied as recommendation degree using the candidate, according to the recommendation
Degree is ranked up to candidate's list of application.
(24) its recommendation degree is deleted from candidate's list of application, and less than appointed threshold value, (such as x, x value can be pre-set
Adjustment, such as default value are application 5), i.e., same sex is filtered out from candidate's list of application and is playing user less than x people's
Using.
(25) judge whether each application in candidate's list of application is installed by targeted customer, if it is from institute
State and the mounted application of the targeted customer is deleted in candidate's list of application.
(26) issuing time respectively applied in candidate's list of application is determined, hair is deleted from candidate's list of application
The cloth time exceedes the application for specifying the time (such as 1 month).
If using attributes such as age, occupations as specified attribute, with above-mentioned position, gender attribute processing mode similarly
It is identical.
The preference information Sexual behavior mode Equations of The Second Kind with targeted customer is recommended to apply, and is exactly to be believed according to the application preferences of user
Breath, such as application installation record, applicating history Download History, using frequency of use, calculates user's application interested,
Pre-download is carried out in the case of user's unaware..
For example, being that user's selection institute Equations of The Second Kind is recommended according to the application preferences information of user in a kind of specific embodiment
Using following steps (31)~(36) can be specifically included:
(31) the application preferences information of targeted customer is obtained, the preference list of application of targeted customer is determined.The application is inclined
Good information for example including：Using installation record, applicating history Download History, using frequency of use etc..According to the application preferences
Information determines the preference list of application of targeted customer.Record is for example installed according to the application of targeted customer, it is determined that installed
Using the preference application for user；And/or determine downloaded application be user preference application；And/or determine frequency of use
Higher than the preference application that the application that appointed threshold value or frequency of use are stood out is user.In an advantageous embodiment,
The preference list of application of user can be determined only according to the application preferences information of (such as nearest one week) in the nearest specified time.
(32) each application in the preference list of application is directed to, determines that (described the whole network refers to institute of the present invention to the whole network
Applicable application download system) downloaded the other application that the user of the application also downloads, using identified other application as
Candidate is applied, and these information can be inquired about from existing the whole network application Download History and obtained；Then the application is determined and described
The common probability of occurrence of candidate's application, the common probability of occurrence refers to the probability that two applications are installed jointly by same user,
The common probability of occurrence value is：(number of users that two applications specified are installed jointly by same user)/total number of users.It is existing
Application download system in there is query interface, number of users that two applications specified are installed jointly by same user and
Total number of users, can inquire about from existing query interface and obtain.
(33) using the common probability of occurrence as recommendation degree, candidate's list of application is carried out according to the recommendation degree
Sequence.
(34) candidate for deleting recommendation degree less than predetermined threshold applies.Application i.e. less than predetermined threshold is not recommended, described
Predetermined threshold can be preset, for example, be defaulted as common probability of occurrence less than 90%.
(35) judge whether each application in candidate's list of application is installed by targeted customer, if it is from institute
State and the mounted application of the targeted customer is deleted in candidate's list of application.
(36) issuing time respectively applied in candidate's list of application is determined, hair is deleted from candidate's list of application
The cloth time exceedes the application for specifying the time (such as 1 month).
Application is recommended (to recommend using user property by the first kind for having obtained finally being recommended after above-mentioned specific processing
Application) list and Equations of The Second Kind recommend application (i.e. using user application preferences recommend application) list.Afterwards, trigger
Terminal where targeted customer downloads the recommended application automatically.The automatic download, refers to do not notifying targeted customer
In the case of carry out reinforming targeted customer after the completion of pre-download, download.
Therefore present invention can ensure that the personal attribute of user and all being covered with two dimensions of application preferences, obtain more accurate
Recommendation, that is, the application recommended and the matching degree of targeted customer be more accurate, and targeted customer need not carry out cumbersome searching again
Operation, improves the operating efficiency that user finds intended application.Simultaneously as the present invention can be pre- in the case of user is unwitting
Download recommended application, can notify user using the form specified after the download is complete, for example can using the simulation box,
The application of download is presented to user by the form of simulation painted eggshell, and user can be mounted directly the application, without waiting for download, therefore this
The described automatic download of invention is also known as smart download.
More specifically, the list for recommending application can be handed down to targeted customer place terminal by the present invention, then
Terminal-pair where triggering targeted customer recommends application selectively to be downloaded.The down operation and follow-up showing interface etc.
Man-machine interactive operation is performed by the client in end side.
, it is necessary to perform automatic down operation after the client in target terminal user obtains the list for recommending application,
But first have to, to recommending list of application to carry out filter operation, specifically include following three kinds of filter operations：
1) need to filter the application installed in this terminal；
2) need to filter by this terminal downloads but uninstalled application；
3) client also needs to do the control of installation kit total size, it is above-mentioned 1) with 2) on the basis of filter out installation kit size
It is more than specified size (such as 150M) application, i.e., only automatic to download the preceding N moneys application for being less than and specifying size (such as 150M).It is described
The size information of installation kit is included in the recommendation list of application information.
Then, client can also judge to need to trigger to download to recommend the application of which of list of application.For example, specific
The automatic trigger condition for downloading recommendation application and operation include following several：
1) the current terminal where targeted customer has been downloaded automatically and the number of old recommendation application before the deadline is
It is no to be less than specified quantity (for example whether less than 3), where the targeted customer is triggered in the case of being judged to being terminal from
It is dynamic to download new recommendation application.The term of validity for example can be：Application is recommended to be downloaded the same day+k day, comprising kth day, with certainly
Right day calculates.
2) for the old recommendation application downloaded automatically more than the term of validity, it is ranked up according to download time；For example such as
Really N number of old recommendation application exceedes the term of validity, then applies the old recommendation for exceeding the term of validity according to the arrangement of download time order, and
Obtain the list of newest N number of recommendation application.Then, subsequent step is performed.
3) one of download time in described having downloaded automatically and old recommendation application more than the term of validity earliest is deleted
Old to recommend application, it is new that terminal where triggering the targeted customer downloads most preceding one of the new sequence recommended in application automatically
Recommend application；Judge whether old recommendation application that is also having downloaded automatically and exceeding the term of validity, if it is repeat this step
Suddenly, this step is otherwise terminated.
For example, if N number of old recommendation application more than the term of validity, then a) first deleting and being downloaded in old recommendation application out of date
Time earliest the 1st, then download new the 1st recommended in list of application and recommend application；B) deleting old recommendation out of date should
Recommend application with the 2nd of middle download time earliest, then the 2nd downloaded in new recommendation list of application；C) by that analogy.
In addition, client also can be set in the present invention downloads the transformation for recommending to apply automatically, such as in one kind tool
In the implement scene of body, following restrictive condition can be included：
1) the simultaneous smart download of client newly recommends the maximum quantity of application to be 3；
2) maximum quantity for newly recommending application by smart download weekly is 6；
If 3) delete old recommendation application, then download same money and recommend application, corresponding number of downloads is still designated as 1.
Certainly, the concrete numerical value of heretofore described setting is all for example, those skilled in the art can also select
Other numerical value are configured.
In a further embodiment, the present invention can also preset the mobile phone state information for allowing to download automatically, in client
End determines whether whether mobile phone state meets the default mobile phone for allowing to download automatically before downloading the recommendation application automatically
State, is downloaded automatically if meeting, otherwise without automatic download.It is illustrated in figure 2 the default permission automatic
The setting interface schematic diagram of the mobile phone state of download, the default mobile phone state for allowing to download automatically for example can be：It is
Whether no connection wifi wireless networks, electricity are sufficient, whether local residual memory space is sufficient, whether mobile phone currently goes out screen etc..
In addition, in a further embodiment, can also handle the foundation and execution of downloading task, specifically include：
Download a task and resettle another task；In downloading process, download management, each list of application in client,
The progress of the invisible smart download of details page；
Processing during abnormal conditions occurs in downloading process, for example, can include following two processing modes：
1) such as the setting schematic diagram of Fig. 3 preset mobile phone states downloaded automatically for termination, as shown in figure 3, working as when detecting
Preceding mobile phone state symbol then stops current automatic download when closing the mobile phone state of default following any termination download, and retains
Current download progress；The mobile phone state for stopping to download includes:Mobile phone terminal electricity is inadequate, wifi disconnectings, available
Memory space inadequate, light screen etc. operation.
2) when recommending the midway of application by user's triggering actively to download in the automatic download, then from currently completed into
Degree starts to continue to download, download management, each list of application, the visible download progress of details page
Can be no matter whether user is with super in a kind of preferred embodiment after the completion of the automatic download
Keeper (root) authority, the recommendation application not to smart download are installed automatically；And in the download management of client
List is invisible；But show installation button in common application list, details page.
When opening a certain page for recommending to apply in client, if recommendation application is carried by user installation
Show that user has installed.As fruit part is recommended using being deleted in advance by user, then not show this in the recommendation information Entry Interface
Money recommends application；If the recommendation application downloaded automatically is all deleted by user, recommendation is not shown in client homepage
Entry Interface is ceased, if pushing the recommendation information Entry Interface of (Push) triggering by message, then the fault-tolerant page is shown.
Introduce in detail further below in the end side of targeted customer using interface notifications users such as recommendation information entrances, and
The embodiment of man-machine interaction is carried out with user.
Client download automatically it is described recommend application after, can be by the button or icon point of client homepage
Hit into the recommendation information Entry Interface.If Fig. 4 is the schematic diagram that a kind of client homepage triggers recommendation information Entry Interface.
Referring to Fig. 4, user can enter " smart download new opplication " scene by clicking on " fine work " icon in the client homepage lower left corner,
I.e. described recommendation information Entry Interface, floating layer is opened after click by animation, and recommendation information Entry Interface is shown in the floating layer.
In addition, after client downloads the recommendation application automatically, can also be by way of sending out notice (Push)
Notify user to have new recommendation application, after user, which clicks on Push, to be notified, then trigger animation and open floating layer, show and push away in the floating layer
Recommend information entry interface.The Push is notified and the automatic behavior for downloading completion can be separated, in a daily period
Whether inquiry meets Push conditions, and the Push conditions can be touched if after having new recommendation application to be downloaded automatically from a web site
Push is sent out to notify.But such Push push frequencies notified can be configured, for example such Push can be set to notify 1
It is at most pushed 1 time, is at most pushed 2 times within 1 week.
Fig. 5 is a kind of schematic diagram of recommendation information Entry Interface of the present invention.Referring to Fig. 5, recommendation information entrance circle
In face, corresponding recommendation application icon is shown according to the actual number for the recommendation application downloaded automatically, when receiving to described
(generally it is click under recommendation information Entry Interface during the browsing instructions of a certain recommendation application in recommendation information Entry Interface
The icon of the recommendation application of hair), then the detail information of recommendation application is shown, the details letter for recommending application is illustrated in figure 6
Breath displaying schematic diagram, which show recommend logic set by prompting word and apply detail information, recommend logic official documents and correspondence
It can pre-set, it is possible to further show icon, title, star of recommendation application etc..Receiving to the recommendation application
Installation instruction when, that is, click on " installations " button described in Fig. 6, then trigger targeted customer place terminal and the recommendation is installed
Using after installation, returning to the interface described in this Fig. 6, " installation " button is shown as " opening ".
If in Fig. 5 or Fig. 6 interface scenario, clicking on the return key of physical keyboard, or the upper right corner " X " is clicked on, that is, moved back
Go out this recommendation information Entry Interface.When exiting, the floating layer of the recommendation information Entry Interface is replaced by pop-up, for example, can point out
Content as shown in Figure 7.The recommendation information Entry Interface is then exited when user clicks on " I is aware of ", is clicked on " cancellation ", pop-up
Disappear, the recommendation information Entry Interface is not exited.After the recommendation information Entry Interface is exited, the floating layer disappears, and returns to
Home interface described in Fig. 4, and after exiting the specified time (after such as 5 seconds), " fine work " icon in Fig. 4 lower left corners disappears,
And deletion has been browsed but uninstalled recommendation application.
In addition, the present invention also needs to the following relevant information reported in the client of targeted customer：
1) when the client of targeted customer is automatically deleted certain and applied, deleted application need to be reported to believe to server end
Breath；Server end (such as 3 months) within the follow-up specified period will not recommend the application to the targeted customer again.
2) completion one is downloaded by smart download to recommend after application, reports downloaded recommendation application message to service
Device end, server end records the recommendation application message, it is to avoid follow-up to repeat to recommend the application.
3) targeted customer's client, which is installed, recommends after application, and installed application message can also be reported to server end,
Server end can count recommendation effect accordingly.
It is corresponding with the above method, the invention also discloses one kind application commending system, for performing side of the present invention
Method.Fig. 8 is a kind of composition schematic diagram of application commending system of the present invention.Referring to Fig. 8, the system includes：
Attribute recommending module 801, the same specified attribute user for determining targeted customer determines that the same specified attribute is used
The mounted application in family, first kind candidate application is used as using identified application；The specified attribute includes：Position, sex, year
Age, and/or occupation；The same specified attribute user is：Its specified attribute and the specified attribute of the targeted customer are with one
User in the range of specified attribute.
Preference recommending module 802, the application preferences information for obtaining targeted customer is determined according to the application preferences information
The preference application of targeted customer；For each described preference application, it is determined that using having downloaded the preference application in download system
The application downloaded of user, be used as Equations of The Second Kind candidate to apply identified application；
Recommending module 803 is selected, meets finger with selection in Equations of The Second Kind candidate application for being applied from the first kind candidate
The application of fixed condition is used as recommendation application；
Automatic download module 804, can be arranged on the client of targeted customer, for triggering the targeted customer place eventually
Automatically the recommendation application is downloaded in end.
Fig. 9 is another composition schematic diagram of the application commending system., in an advantageous embodiment, should referring to Fig. 9
System further comprises that recommendation information enters mouth mold, 085, the recommendation information inlet module 805 is specifically included：
Showing interface module 851, for the terminal display recommendation information Entry Interface where the targeted customer, is pushed away at this
Recommend the information that the recommendation application downloaded automatically is shown in information entry interface；
Respond module 852, is received to the clear of a certain recommendation application in the recommendation information Entry Interface for working as
Look at when instructing (icon for being generally click on recommendation application), then show the detail information of recommendation application；This is pushed away receiving
When recommending the installation instruction of application, terminal where triggering the targeted customer installs the recommendation application；
Processing module 853 is exited, for after the recommendation information Entry Interface is exited, deletion have been browsed but uninstalled
It is described to recommend application.
In a kind of specific embodiment, it is described selection recommending module 803 specifically for：Judge the first kind candidate application
Whether each application in being applied with Equations of The Second Kind candidate is installed by targeted customer, is if it is applied from the first kind candidate
The mounted application of the targeted customer is deleted with Equations of The Second Kind candidate application；And/or, determine that the first kind candidate applies and the
The issuing time respectively applied in two class candidates application, deletes the application that issuing time exceedes the time of specifying；By remaining described
One class candidate is applied and Equations of The Second Kind candidate is applied as recommendation application.
In having a kind of specific embodiment, the recommending module 803 of selecting is further used for：Determine that the first kind candidate should
Installation number of users in the same specified attribute user, with the installation number of users to the first kind candidate using arranging
Sequence, deletes in being applied from first kind candidate and installs the application that number of users is less than specified threshold；Determine the Equations of The Second Kind candidate application
In the common probability of occurrence applied with the preference of application, Equations of The Second Kind candidate application is carried out with the common probability of occurrence
Sequence, deletes the application that the common probability of occurrence is less than specified threshold in being applied from Equations of The Second Kind candidate.
In a kind of specific embodiment, the automatic download module 804 is specifically for receiving the list for recommending to apply
Whether information, terminal where triggering the targeted customer is judged in the recommendation list of application including answering that this terminal has been installed
With, downloaded application or the size of installation kit be more than the application of predetermined threshold, if it is, recommending application row from described
The size that application, downloaded application or installation kit that described terminal has been installed are deleted in table is more than predetermined threshold
Using；Terminal where triggering the targeted customer downloads sorted in the recommendation list of application first N application, the N automatically
For default natural number.
In another specific embodiment, the automatic download module 804 specifically for：Judge the targeted customer place
Terminal has been downloaded automatically and whether old recommendation application number before the deadline is less than specified quantity, in the feelings for being judged to being
Terminal where the targeted customer is triggered under condition downloads new recommendation application automatically.
The terminal where the targeted customer is triggered in the case of being judged to being downloads new recommendation application automatically, tool
Body includes：
Old recommendation downloaded automatically to terminal where the targeted customer and more than the term of validity is applied according to download
Time is ranked up；
The Geju City of download time earliest in old recommendation application downloaded automatically described in deleting and more than the term of validity
Recommend application, terminal where triggering the targeted customer is downloaded most preceding one of the new sequence recommended in application and newly pushed away automatically
Recommend application；Judge whether old recommendation application that is also having downloaded automatically and exceeding the term of validity, if it is repeat this step
Suddenly, this step is otherwise terminated.
In addition, each functional module in each embodiment of the invention can be integrated in a processing unit, can also
That modules are individually physically present, can also two or more modules it is integrated in a unit.Above-mentioned integrated list
Member can both be realized in the form of hardware, it would however also be possible to employ the form of SFU software functional unit is realized.The work(of each embodiment
Energy module can be located at a terminal or network node, or can also be distributed on multiple terminals or network node.
In addition, each embodiment of the present invention can pass through the data processing by data processing equipment such as computer execution
Program is realized.Obviously, data processor constitutes the present invention.In addition, being generally stored inside the data in a storage medium
Processing routine by program by directly reading out storage medium or by installing or copying to data processing equipment by program
Performed in storage device (such as hard disk and/or internal memory).Therefore, such storage medium also constitutes the present invention.Storage medium can be with
Using any kind of recording mode, such as paper storage medium (as paper tape), magnetic storage medium (such as floppy disk, hard disk, flash memory
Deng), optical storage media (such as CD-ROM), magnetic-optical storage medium (such as MO) etc..
Therefore the invention also discloses a kind of storage medium, wherein the data processor that is stored with, the data processor
Any embodiment for performing the above method of the present invention.
In addition, method and step of the present invention with data processor except that can be realized, can also by hardware Lai
Realize, for example, can be by gate, switch, application specific integrated circuit (ASIC), programmable logic controller (PLC) and embedded microcontroller
Etc. realizing.Therefore this hardware that can realize the method for the invention can also constitute the present invention.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all essences in the present invention
God is with principle, and any modification, equivalent substitution and improvements done etc. should be included within the scope of protection of the invention.
Claims (10)
1. one kind application recommendation method, it is characterised in that including：
The same specified attribute user of targeted customer is determined, the mounted application of same specified attribute user is determined, to be determined
Application be used as the first kind candidate application；
The application preferences information of targeted customer is obtained, the preference application of targeted customer is determined according to the application preferences information；For
Each preference application, it is determined that the application downloaded using the user that preference application has been downloaded in download system, will be determined
Application be used as Equations of The Second Kind candidate application；
Selection in being applied with Equations of The Second Kind candidate is applied to meet the application of specified requirements as recommendation application from the first kind candidate；
Terminal where triggering the targeted customer downloads the recommendation application automatically；
The application for meeting specified requirements with selection in Equations of The Second Kind candidate application is being applied to be answered as recommendation from the first kind candidate
Used time, this method further comprises：
The common probability of occurrence that the application in the Equations of The Second Kind candidate application is applied with the preference is determined, it is general with the common appearance
Rate is ranked up to Equations of The Second Kind candidate application, and the common probability of occurrence is deleted from Equations of The Second Kind candidate application less than specified
The application of threshold value；The common probability of occurrence refers to the probability that two applications are installed jointly by same user；This occurs jointly
Probable value is：The number of users that two applications specified are installed jointly by same user/total number of users.
2. according to the method described in claim 1, it is characterised in that described to be applied from first kind candidate and Equations of The Second Kind candidate application
It is middle to select to meet the application of specified requirements as application is recommended, specifically include：
Judge that the first kind candidate applies whether each application in being applied with Equations of The Second Kind candidate is installed by targeted customer, such as
Fruit is to be applied from the first kind candidate and delete the mounted application of the targeted customer with Equations of The Second Kind candidate application；And/or,
The issuing time that the first kind candidate applies and respectively applied in Equations of The Second Kind candidate application is determined, deletion issuing time, which exceedes, specifies
The application of time；
The remaining first kind candidate is applied and Equations of The Second Kind candidate applies and is used as recommendation application.
3. according to the method described in claim 1, it is characterised in that should with Equations of The Second Kind candidate being applied from the first kind candidate
When the application for meeting specified requirements with middle selection is applied as recommendation, this method further comprises：
Determine that the first kind candidate applies the installation number of users in the same specified attribute user, with the installation number of users pair
The first kind candidate deletes in being applied from first kind candidate using being ranked up and installs number of users answering less than specified threshold
With.
4. according to the method described in claim 1, it is characterised in that terminal where the triggering targeted customer is downloaded automatically
It is described to recommend application, specifically include：
The list information for recommending application is sent to targeted customer place terminal,
Whether terminal where triggering the targeted customer is judged in the recommendation list of application including answering that this terminal has been installed
With, downloaded application or the size of installation kit be more than the application of predetermined threshold, if it is, recommending application row from described
The size that application, downloaded application or installation kit that described terminal has been installed are deleted in table is more than predetermined threshold
Using；
Terminal where triggering the targeted customer downloads first N application of being sorted in the recommendation list of application automatically, and the N is
Default natural number.
5. according to the method described in claim 1, it is characterised in that terminal where the triggering targeted customer is downloaded automatically
It is described to recommend application, specifically include：
Terminal where judging the targeted customer is downloaded automatically and whether old recommendation application number before the deadline is less than
Specified quantity, the terminal where the targeted customer is triggered in the case of being judged to being downloads new recommendation application automatically.
6. method according to claim 5, it is characterised in that described that the target use is triggered in the case where being judged to being
Terminal where family downloads new recommendation application automatically, specifically includes：
Old recommendation downloaded automatically to terminal where the targeted customer and more than the term of validity was applied according to download time
It is ranked up；
The Geju City recommendation of download time earliest in old recommendation application downloaded automatically described in deleting and more than the term of validity
Using terminal where triggering the targeted customer is automatic to download the most preceding new recommendation application of sorting newly recommended in application；
Judge whether old recommendation application that is also having downloaded automatically and exceeding the term of validity, if it is repeat this step, otherwise tie
This step of beam.
7. according to the method described in claim 1, it is characterised in that this method terminal where the targeted customer is triggered is automatic
Download after the recommendation application, further comprise：
The terminal display recommendation information Entry Interface where the targeted customer, shows institute certainly in the recommendation information Entry Interface
The information of the dynamic recommendation application downloaded；
When receiving the browsing instructions to a certain recommendation application in the recommendation information Entry Interface, then the recommendation is shown
The detail information of application；When receiving the installation instruction applied to the recommendation, terminal where triggering the targeted customer is installed should
Recommend application；
After the recommendation information Entry Interface is exited, deletion has been browsed but the uninstalled recommendation application.
8. the method according to any one of claim 1~7, it is characterised in that
The specified attribute includes：Position, sex, age, and/or occupation；
The same specified attribute user is：Its specified attribute and the specified attribute of the targeted customer are with a specified attribute model
Enclose interior user.
9. one kind application commending system, it is characterised in that including：
Attribute recommending module, the same specified attribute user for determining targeted customer determines that the same specified attribute user has pacified
The application of dress, first kind candidate application is used as using identified application；
Preference recommending module, the application preferences information for obtaining targeted customer determines that target is used according to the application preferences information
The preference application at family；For each preference application, it is determined that using under the user institute that preference application has been downloaded in download system
The application of load, identified application is applied as Equations of The Second Kind candidate；
Recommending module is selected, meets specified requirements with selection in Equations of The Second Kind candidate application for being applied from the first kind candidate
Applied using as recommendation, including：Determine that application in Equations of The Second Kind candidate application and the preference are applied common
Probability of occurrence, is ranked up with the common probability of occurrence to Equations of The Second Kind candidate application, is deleted from Equations of The Second Kind candidate application
The common probability of occurrence is less than the application of specified threshold；The common probability of occurrence refers to that two applications are total to by same user
With the probability installed；The common probability of occurrence value is：The number of users that two applications specified are installed jointly by same user/total
Number of users；
Automatic download module, terminal where for triggering the targeted customer downloads the recommendation application automatically.
10. system according to claim 9, it is characterised in that the system further comprises recommendation information inlet module, should
Recommendation information inlet module is specifically included：
Showing interface module, for the terminal display recommendation information Entry Interface where the targeted customer, in the recommendation information
The information for the recommendation application downloaded automatically is shown in Entry Interface；
Respond module, for working as a certain browsing instructions for recommending to apply received in the recommendation information Entry Interface
When, then show the detail information of recommendation application；When receiving the installation instruction applied to the recommendation, the targeted customer is triggered
Place terminal installs the recommendation application；
Processing module is exited, for after the recommendation information Entry Interface is exited, deletion has been browsed but uninstalled described pushed away
Recommend application.
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| Application Number | Priority Date | Filing Date | Title |
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| CN201410785047.3A CN104601659B (en) | 2014-12-17 | 2014-12-17 | Using recommendation method and system |
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| CN201410785047.3A CN104601659B (en) | 2014-12-17 | 2014-12-17 | Using recommendation method and system |
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| CN104601659B true CN104601659B (en) | 2017-10-03 |
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Families Citing this family (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104994147B (en) * | 2015-06-24 | 2018-04-17 | 上海卓悠网络科技有限公司 | The recommendation method of software download, system and the server-side being applicable in and user equipment |
| CN105227445B (en) * | 2015-10-23 | 2018-09-14 | 中国联合网络通信集团有限公司 | Recommend platform using methods and applications are recommended |
| CN106909402B (en) * | 2015-12-22 | 2020-08-28 | 北京奇虎科技有限公司 | Application program processing method and device |
| CN106909584B (en) * | 2015-12-23 | 2021-09-07 | 北京奇虎科技有限公司 | Game information pushing method and device based on mobile terminal |
| CN105787759A (en) * | 2016-02-23 | 2016-07-20 | 北京金山安全软件有限公司 | Method and device for acquiring user attribute and electronic equipment |
| CN107566314B (en) * | 2016-06-30 | 2021-05-14 | 斑马智行网络(香港)有限公司 | Data transmission system, method and equipment |
| CN106250427B (en) * | 2016-07-25 | 2020-02-07 | 浪潮(北京)电子信息产业有限公司 | Method and system for generating container mirror image recommendation information |
| CN106844612B (en) * | 2017-01-17 | 2021-04-09 | 阿里巴巴（中国）有限公司 | Method and device for recommending hotwords based on user installed application |
| CN107291859A (en) * | 2017-06-09 | 2017-10-24 | 深圳市金立通信设备有限公司 | A kind of method and terminal for managing application |
| CN107612974B (en) * | 2017-08-23 | 2020-04-17 | Oppo广东移动通信有限公司 | Information recommendation method and device, mobile terminal and storage medium |
| CN107908411A (en) * | 2017-11-17 | 2018-04-13 | 广东小天才科技有限公司 | Application program management method and service equipment |
| CN107948435A (en) * | 2017-12-04 | 2018-04-20 | 程桂平 | Method and system based on user personality selection application |
| CN108320208B (en) * | 2017-12-22 | 2021-12-28 | 金瓜子科技发展（北京）有限公司 | Vehicle recommendation method and device |
| CN109729419B (en) * | 2018-12-26 | 2021-09-21 | 上海众源网络有限公司 | Push video preloading method and device, electronic equipment and storage medium |
| CN110175298B (en) * | 2019-04-12 | 2023-11-14 | 腾讯科技（深圳）有限公司 | User matching method |
| CN110503478B (en) * | 2019-08-26 | 2020-08-18 | 北京深演智能科技股份有限公司 | APP pushing method and device |
| CN111209033B (en) * | 2020-01-10 | 2024-01-12 | 百度在线网络技术（北京）有限公司 | Method for downloading small program package and related equipment |
| CN113553820A (en) * | 2020-04-24 | 2021-10-26 | 腾讯科技（深圳）有限公司 | Information processing method, equipment and computer readable storage medium |
| CN111784174B (en) * | 2020-07-10 | 2022-09-20 | 上海淇毓信息科技有限公司 | Method and device for managing risk policy based on user portrait and electronic equipment |
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