CN103744849B - Method and device for automatic recommendation application - Google Patents
Method and device for automatic recommendation application Download PDFInfo
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- CN103744849B CN103744849B CN201310462445.7A CN201310462445A CN103744849B CN 103744849 B CN103744849 B CN 103744849B CN 201310462445 A CN201310462445 A CN 201310462445A CN 103744849 B CN103744849 B CN 103744849B
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Abstract
The invention provides a method and device for automatic recommendation application. The method includes the steps of collecting user access information, dividing categories which the user access information belongs to, searching for matched applications in an application data set of preset corresponding categories according to the user access information and the categories of the user access information, generating application files corresponding to the categories and putting the searched applications of the categories in the corresponding application files to carry out recommendation. According to the method and device, individualized demands of users can be met, and recommendation efficiency and the coverage rate are improved.
Description
Present patent application is the applying date on December 27th, 2011, Application No. 201110444074.0, entitled
The divisional application of the Chinese invention patent application of " method and device that a kind of application is recommended automatically ".
Technical field
The application is related to technical field of information processing, method and a kind of application that more particularly to a kind of application is recommended automatically
Automatically the device recommended.
Background technology
Internet is the important channel that people obtain information, and the user that is mainly characterized by of conventional internet finds certainly
During oneself things interested, need to carry out substantial amounts of search by browser, while needing artificially to filter out a large amount of uncorrelated
Result, it is cumbersome, and expend time and efforts.
With developing rapidly for Internet technology, people are also more next to the demand of various network applications (Application)
It is more extensive, but with the increase of demand, the terminal applies that people install in terminal clientsaconnect are also more and more, various to apply
The deployment of client is more and more too fat to move huge, and this not only causes the waste to terminal resource, nor is easy to management.Even if adopting
Deployment management is carried out with client-server architecture, server end also lacks to subsequently using after the deployment for completing client
Managerial ability.
Although occurring in that the concept of so-called " thin-client (Thin Client) " now, thin-client is by its mouse, keyboard
Server process is sent to Deng input, server is back to client and shows result again.But this tupe is restricted
In network transfer speeds, and the disposal ability of server etc. is limited, therefore, it is more the commercial local for being applied to enterprise-level
In net, the entertainment requirements of domestic consumer are also not suitable at present.
To make user obtain more preferable experience, prior art proposes and provides the user application interested and push away automatically
The scheme recommended, i.e., be located by knowing the interest of user, is actively its recommendation, is provided its application interested.However, this should
With the mode recommended, recommended by hand by editorial staff, the mode that this editorial staff recommends by hand is mainly deposited
In following defect：
1st, efficiency is too low, too low for the recommendation coverage rate of application, for example, for application hundreds thousand of on platform, daily
Using artificial recommendation, can only also recommend hundreds of.If want to recommend all using actually cannot realizing, and coverage rate is too
It is low, because proportion is too low.
2nd, it is this to recommend the unified recommendation principle for being based entirely on editorial staff to carry out, nothing the same for each user
Method meets the demand of user individual.Because some applications recommended are suitable for certain user, and for some
User does not but like.
Therefore, the technical problem that those skilled in the art urgently solve is needed to be exactly at present：Propose a kind of application certainly
The dynamic mechanism recommended, to meet the individual demand of user, and improves recommendation efficiency and coverage rate.
The content of the invention
Technical problems to be solved in this application are to provide a kind of method that application is recommended automatically, to meet the individual of user
Property demand, and improve recommendation efficiency and coverage rate.
Present invention also provides the device that a kind of application is recommended automatically, to ensure said method application in practice and
Realize.
In order to solve the above problems, the embodiment of the present application discloses a kind of method that application is recommended automatically, specifically can wrap
Include：
Collection user access information；
Divide the classification that the user access information is belonged to；
According to the user access information and its classification, in the application data sets of preset corresponding classification matching is searched
Using；
The corresponding application file folder of each classification is generated, the application of each classification for being found is put into into corresponding application
Recommended in file.
Preferably, the user access information includes the local operation access information of user, and/or, user's is online
Operational access information.
Preferably, the step of classification that the division user access information is belonged to, can include：
Extract the Main classification label and the corresponding operation frequency in the user access information；
The Main classification label is converted to into corresponding applicating category by default correlation rule；The default association rule
The transformation rule of tag along sort and applicating category based on then；
The operation frequency of each applicating category correspondence Main classification label is counted, by each applicating category by the operation frequency for being counted
It is ranked up from high to low；
Extract the front n applicating category of predetermined number, the classification belonged to by active user's access information；Wherein, the n
It is the positive integer more than 1.
Preferably, the application of the application data sets has Main classification label and at least one-level subclassification label, respectively
The other application data set of species is made up of respectively the application with same Main classification label；
The foundation user access information and its classification, in the application data sets of preset corresponding classification matching is searched
Using the step of may further include：
The classification belonged to according to the user access information determines the application data set of correspondence classification；
Extract the subclassification label of the user access information；
In the application data sets of the correspondence classification, using subclassification label and the application of the user access information
The subclassification label of corresponding level is matched, and obtains the application of matching and corresponding weight；
Front m application is chosen from high to low as answering that the application data sets of current class are matched according to the weight
With, wherein, the m is the positive integer more than 1.
Preferably, the weight can include：Matching value between subclassification label, or, between subclassification label
Matching value and application correlation.
Preferably, described method, can also include：
By the operation frequency of each applicating category correspondence Main classification label, arrange application file folder represents order；
Represent the application file folder on the desktop of user equipment by the order that represents；
In each application file folder, by the weight of application the application is represented from high to low.
Preferably, described method, can also include：
User is obtained for the operation information for recommending to apply, the weight of correspondence application is accordingly adjusted.
Preferably, described method, can also include：
Operation information of the user for application file folder is obtained, accordingly adjust application file folder represents order.
Preferably, described method, can also include：
User access information according to being gathered sets up user characteristics storehouse；
By user for the operation information for recommending to apply, the user characteristics storehouse is write.
The application also discloses the device that a kind of application is recommended automatically, specifically can include：
User accesses acquisition module, for gathering user access information；
User's access level division module, for dividing the classification that the user access information is belonged to；
Searching modul is applied in matching, for according to the user access information and its classification, in preset corresponding classification
Application data sets search the application of matching；
Recommending module is applied in matching, for generating the corresponding application file folder of each classification, by each class for being found
Other application is put in corresponding application file folder to be recommended.
Preferably, the user access information includes the local operation access information of user, and/or, user's is online
Operational access information.
Preferably, user's access level division module can include：
Feature information extraction submodule, for extracting the user access information in Main classification label and corresponding operation
The frequency；
Classification correspondence submodule, for the Main classification label to be converted to into corresponding application class by default correlation rule
Not；The transformation rule of tag along sort and applicating category based on the default correlation rule；
Sorting sub-module, for counting the operation frequency of each applicating category correspondence Main classification label, each applicating category is pressed
The operation frequency for being counted is ranked up from high to low；
Sort out submodule, for extracting the front n applicating category of predetermined number, belonged to by active user's access information
Classification；Wherein, the n is the positive integer more than 1.
Preferably, the application of the application data sets has Main classification label and at least one-level subclassification label, respectively
The other application data set of species is made up of respectively the application with same Main classification label；
The matching may further include using searching modul：
Application data set determination sub-module, the classification for being belonged to according to the user access information determines correspondence classification
Application data set；
Tag extraction submodule, for extracting the subclassification label of the user access information；
Tag match submodule, in the application data sets of the correspondence classification, using the user access information
Subclassification label matched with the subclassification label of corresponding level of application, obtain the application of matching and corresponding weight；
Using submodule is chosen, for choosing front m application answering as current class from high to low according to the weight
With in data set match application, wherein, the m is the positive integer more than 1.
Preferably, the weight can include：Matching value between subclassification label, or, between subclassification label
Matching value and application correlation.
Preferably, described device, can also include：
Application file folder sequence display module, for by the operation frequency of each applicating category correspondence Main classification label, arranging
What application file was pressed from both sides represents order；And represent the application file folder on the desktop of user equipment by the order that represents；
Using sequence display module, in each application file folder, by the weight of application described answering being represented from high to low
With.
Preferably, described device, can also include：
Weight adjusting module, for obtaining user for the operation information for recommending to apply, accordingly adjusts correspondence application
Weight.
Preferably, described device, can also include：
Application file folder order adjusting module, for obtaining operation information of the user for application file folder, corresponding adjustment
What application file was pressed from both sides represents order.
Preferably, described device, can also include：
Feature database sets up module, for setting up user characteristics storehouse according to the user access information for being gathered；
Feature database writing module, for the operation information for recommending to apply, the user characteristics storehouse is write for by user.
Compared with prior art, the application has advantages below：
The application is sorted out according to user access information, forms the application file folder of respective classes, is then based on described
Classification searches the application of matching in the application data sets of correspondence classification, and these applications are put in the file of correspondence classification
Row is recommended, and so as to set up contact between application and user, fully meets the individual demand of user, and effectively increase should
Recommendation efficiency and coverage rate.
Furthermore, the application directly passes through application using user interface as entrance on interface or by the link on interface
Folder icon is recommended to apply to user, so as to the application needed for the faster easier acquisition of user, is convenient for users to operate；And
And, can point out user the use to the application by way of icon is as using entrance, but really select to use in user
Before, not actual installation this apply corresponding configuration file, as such, it is possible to using it is front it is not excessive occupancy client money
Source.Additionally, the icon in user interface can concentrate deployment or push by network side central server, malice journey is This prevents
Sequence arbitrarily adds malice icon in interface, further increases security.
Description of the drawings
Fig. 1 is the flow chart of the embodiment of the method 1 that a kind of application of the application is recommended automatically；
Fig. 2 is the flow chart of the embodiment of the method 2 that a kind of application of the application is recommended automatically；
Fig. 3 is the structured flowchart of the device embodiment that a kind of application of the application is recommended automatically.
Specific embodiment
It is understandable to enable the above-mentioned purpose of the application, feature and advantage to become apparent from, it is below in conjunction with the accompanying drawings and concrete real
Apply mode to be described in further detail the application.
The core idea of the embodiment of the present application is to be sorted out according to user access information, forms answering for respective classes
With file, the application that the classification searches matching in the application data sets of correspondence classification is then based on, these applications are put
Recommended in the file for entering correspondence classification, so as to set up contact between application and user.
With reference to Fig. 1, flow chart the step of it illustrates the embodiment of the method that a kind of application of the application recommends automatically, specifically
May include steps of：
Step 101, collection user access information；
Used as a kind of example of the embodiment of the present application concrete application, the user access information can include that user's is local
Operational access information, and/or, the online operational access information of user.
The user access information can be acquired by the client software installed on a user device, wherein, it is described
User equipment can include all kinds of intelligent terminals such as computer, notebook computer, mobile phone, PDA, panel computer.It is presented below several
The local operation access information of collection user is planted, and/or, the example of the online operational access information of user：
Example 1, by browser user's online operational access information interior for a period of time, including the network address and phase of access are gathered
Access times answered etc.；
Such as gathering the online operational access information in user 15 days by browser is：
| Access network address | Access times |
| 4939.com | 31 |
| Qiyi.com | 2 |
| Youku.com | 7 |
| 7k7k.com | 4 |
Example 2, gathers the local operation access information of user, such as by adopting by the fail-safe software installed on a user device
Online operational access information and local IP access information in collection user 15 days is：MPC and its number of times are opened, certain is opened
Game and its number of times etc..
Certainly, the method for above-mentioned collection and the information of collection are only used as example, and those skilled in the art are according to actual feelings
It is feasible that condition gathers required user access information using any one mode, and the embodiment of the present application is to this without the need for be limited
System.
The classification that step 102, the division user access information are belonged to；
In a preferred embodiment of the present application, the step 102 can specifically include following sub-step：
Sub-step S11, the Main classification label and the corresponding operation frequency extracted in the user access information；
Sub-step S12, the Main classification label is converted to into corresponding applicating category by default correlation rule；It is described pre-
If correlation rule based on tag along sort and applicating category transformation rule；
Sub-step S13, the operation frequency for counting each applicating category correspondence Main classification label, by each applicating category by being counted
The operation frequency be ranked up from high to low；
Sub-step S14, the front n applicating category for extracting predetermined number, the classification belonged to by active user's access information；
Wherein, the n is the positive integer more than 1.
In practice, can be led to according to the basic classification (applicating category) that application file folder is pre-set by technical staff
Analysis user access information is crossed, the application file folder basic classification that user access information meets is obtained.For example, what is pre-set should
There are 20 with file basic classification, and pass through to analyze user access information, discovery there are some basic classifications for active user
Unwanted, then can divide the classification that user access information belonged to be more be close to the users before 3 of access habits
Or 5.For example, video, game, education etc..
The local operation access information of the user and online operational access information would generally carry label (tag) information,
For example, it is neat with the fiery shadow person of bearing, animation, serial, illusion, risk, bank sheet for the video that user is opened in local operation
The label informations such as history；Or such as, for the network address that user is accessed on the net, with video, film, comedy movie, comedy king
Deng label information.
Main classification label is determined in the label obtained from the user access information, as above the animation in example or film,
Matched with the application file folder basic classification for pre-setting, judged which kind of application file folder point Main classification label should belong to
In class.For example, Main classification label is set and the transformation rule of applicating category is as shown in the table：
Using above-mentioned transformation rule, then Main classification label " animation " or " film " in example is gone up, be can be exchanged into corresponding
Applicating category is " video ", that is, determine and pressed from both sides using the application file of visual classification.
For example：(1) user's net shield data of nearest 15 days are extracted：Main classification label can be included in data11, data11
Interest and operation frequency weight：Such as：
| interest | weight |
| novel-dm | 1 |
| comic-dm | 4 |
| 4399-dm | 1 |
(2) by from the Main classification label of net shield extracting data, by default transformation rule table
(yunCatToZhuoMianCat.conf) basic classification of the user interest being converted under application file folder taxonomic hierarchies, will
Main classification label is converted to corresponding applicating category.The default transformation rule table yunCatToZhuoMianCat.conf lattice
Can include in formula：The information of Main classification label, applicating category title and applicating category id.Such as：
| Main classification label | Applicating category title | Applicating category id |
| 4399-dm | Game | 5 |
| comic-dm | Fashion is entertained | 8 |
| novel-dm | Novel | 11 |
(3) the operation frequency of each applicating category correspondence Main classification label is counted, by each applicating category by the operation for being counted
The frequency is ranked up from high to low；Front 9 applicating categories of extraction, the classification belonged to by active user's access information, i.e., finally
The classification application file of displaying.Such as：
| Main classification label | Applicating category title | Applicating category id | weight |
| comic-dm | Fashion is entertained | 8 | 4 |
| novel-dm | Novel | 11 | 1 |
| 4399-dm | Game | 5 | 1 |
According to this example, determine that classification that active user's access information is belonged to is fashion amusement, novel, game, i.e., subsequently
Fashion amusement, novel, the application file folder of three kinds of classification of game can accordingly be generated.
In implementing, if divided classification is analyzed to user access information is unable to reach specified quantity, such as
Three classifications can be only generated using upper example, it is impossible to meet the demand of 9 applicating categories, then the network that can be counted according to high in the clouds
The most applicating category of the actually used number of times of user or most newly-installed applicating category carry out polishing as the applicating category recommended,
For example, for upper example, video, education, picture, music, children, utility this 6 applicating categories can be further added by.
Certainly, the method for above-mentioned division user access information institute belonging kinds is solely for example, those skilled in the art
All it is feasible using a kind of mode according to actual conditions, for example, does not extract Main classification label, directly by user access information institute
The label of band is converted to applicating category according to presetting rule；Or, extracting directly Main classification label as applicating category etc., this Shen
Please this is not restricted.
Step 103, according to the user access information and its classification, look in the application data sets of preset corresponding classification
Look for the application of matching；
The application (Application) refers to the various services that user is used on network, such as application program, net
Page, video, novel, music, game, news, shopping and mailbox etc..Application data set includes multiple applications, opens from each
It is laid flat platform.Some labels can be taken using itself, in the embodiment of the present application, the label can be classified, that is, be divided into master
Tag along sort and subclassification label, wherein, the subclassification label can be further divided into multiple ranks.For example, Main classification
Label is video, and first order subclassification label is film, and second level subclassification label is comedy movie, horrow movie or action electricity
Shadow etc..That is, the application of the application data sets has Main classification label and at least one-level subclassification label, it is various types of
Other application data set is made up of the application with same Main classification label respectively, and for example, some applications are all with video
Main classification label, then combine these applications, forms the other application data set of video class.
In a kind of preferred embodiment of application, the step 103 may further include following sub-step：
Sub-step S21, the classification belonged to according to the user access information determine the application data set of correspondence classification；
For example, the classification that active user's access information is belonged to be fashion amusement, novel, game, it is determined that application number
Include the data that the application of the Main classification label that fashion entertains the application data set of classification, i.e., with fashion amusement is constituted according to collection
Collection；The application data set of novel classification, i.e., the data set that the application of the Main classification label with novel is constituted；Game class is other
Application data set, i.e., the data set that the application with the Main classification label played is constituted.
Sub-step S22, the subclassification label for extracting the user access information；
As it was previously stated, the local operation access information of the user and online operational access information would generally carry label
(tag) information, for example, for the video that user is opened in local operation, with the fiery shadow person of bearing, animation, serial, illusion,
The label informations such as risk, bank Ben Qishi；Or such as, for the network address that user is accessed on the net, with video, film, comedy electricity
The label informations such as shadow, the king of comedy.
Subclassification label is extracted in the label information of these user access informations, as above in example, one-level can be extracted
Subclassification label：Serial, animation, film, two grades of subclassification labels：Illusion, risk, comedy movie, three-level subclassification label：
The fiery shadow person of bearing, bank Ben Qishi, the king of comedy.Those skilled in the art divide the subclassification label of multiple ranks according to actual conditions
All it is feasible, the application is not restricted to this.It should be noted that using the present embodiment, needing the son for dividing at least one-level
Tag along sort, to carry out follow-up tag match.
Sub-step S23, it is described correspondence classification application data sets, using the subclassification mark of the user access information
Sign and matched with the subclassification label of the corresponding level of application, obtain the application of matching and corresponding weight；According to the power
Weight chooses from high to low the application that front m application is matched as the application data sets of current class, wherein, the m is more than 1
Positive integer.
Due to the application data sets in certain classification, often there are thousands of applications, sub-step S23 is led to
Cross tag match algorithm and calculate the subclassification label of user access information in answering that the application data sets of correspondence classification are matched
With.Used as the specific example of the embodiment of the present application, the weight can include：Matching value between subclassification label, i.e., for example,
Calculate the matching of the subclassification label of the subclassification label of user access information and the application data sets application of correspondence classification
Value, or, the correlation of matching value and application between subclassification label, the correlation refer to every daily downloads of application and
The assessment parameter of user's scoring.
Used as another example of the present embodiment concrete application, sub-step S23 may further include following sub-step：
The subclassification label of sub-step S23-1, foundation user access information, in the application data sets of the correspondence classification
Retrieval character related application, the feature related application is identical with the subclassification label segment of user access information or whole phases
The application of same subclassification label；
In the present embodiment, user access information includes subclassification label, and by the subclassification label with application
Matching, retrieves feature related application.
The son point of sub-step S23-2, the subclassification label for calculating the feature related application and active user's access information
The matching value of class label；
In concrete implementation, certain matching value can be given by the subclassification label of user access information, and by this
A little tag along sort is divided into different groups, and the matching value with group subclassification label is the same.
For example, the subclassification label of active user's access information is as shown in the table：
| TV play | Comedy | Love | The story of a play or opera | Bao Jianfeng | Jin Sha | Li Jichang |
Next a matching value is distributed to the subclassification label that each is organized, as above these subclassification labels are divided into 4 by example
Group and giving obtain after one matching value of each subclassification label：
TV play 60
Comedy 6, love 6, the story of a play or opera 6
Protect sword cutting edge of a knife or a sword 2, Jin Sha 2
Li Ji prosperous 1
Next, by the subclassification label of the subclassification label of the feature related application found and active user's access information
Contrasted, by subclassification tag hit situation the matching value of each feature related application is calculated, wherein, hit rate (hit
Tag group numbers/total tag groups) and hit matching value ratio (the weights sum of hit/weights are total) respective weight can be root
It is adjusted according to business rule, summation is 100.Wherein tag refers to subclassification label.Such as video is 50:50, video class
The matching value computing formula of feature related application is：
Weight=(the tag group numbers of hit/total tag groups) * 50+ (the matching value sum of hit/matching value sum) * 50；
It should be noted that there is a hit to can be regarded as the group hit in tag groups, matching value can round up.
As above example, searching the tag of certain feature related application is:
| TV play | Other | Love | The story of a play or opera | Liu Dehua | Jin Sha | Li An | Other | 2011 | Continent |
By the subclassification label contrast of itself and active user's access information it can be found that the tag of hit has a TV play, love,
The story of a play or opera, Jin Sha has 3 groups (classification, type are acted the leading role) hit, then the matching value of the application is exactly weight=3/4*50+74/
83*50=68 (67.17 round up 68).
Sub-step S23-3, feature related application is ranked up according to matching value is descending；
After calculating the matching value of each feature related application, can from big to small be ranked up by matching value.In order to every
The application of secondary taking-up is unlikely to focus on that certain is several, allows those applications compared rearward recommended can also arrive, can respectively from
In the several matching values interval set in advance, choose the application that falls in the interval of certain amount matching value to recommend, for example from
3 are selected in matching interval 100-88,2 are selected from 87-73,1 is selected from 72-16.Wherein, in same interval interior, matching value
High is preferentially selected.If the not enough quantity of application in certain interval, supply from low interval selection thed close on.
Sub-step S23-4, according to the sequence, extract predetermined number, matching value corresponds with multiple pre-set intervals
Feature related application, as the application of matching.
In implementing, when the matching value of multiple feature related applications is equal, sub-step S23 can also be wrapped
Include：
The matching value of the subclassification label of sub-step S23-5, the calculating feature related application and user access information, with
And the correlation of equal each feature related application of matching value and the subclassification label of active user's access information.
In the case where the matching value of multiple feature related applications is the same, the feature correlation for calculating identical match value is needed to answer
With the correlation with the subclassification label of active user's access information.
For example, it is assumed that the application A related to the subclassification label of active user's access information, using B, using the matching of C
Value is identical, and calculating process can be as follows：
The download of the download+C of the download+B of total download=A；
The scoring of the scoring+C of the scoring+B of overall score=A；
It is using the correlation of A：Scoring/overall score the * 40 of the download of A.assoc=A/total download * 60+A；
It is using the correlation of B：Scoring/overall score the * 40 of the download of B.assoc=B/total download * 60+B；
It is using the correlation of C：Scoring/overall score the * 40 of the download of C.assoc=C/total download * 60+C.
Sub-step S22-5, feature related application is ranked up from big to small according to matching value, wherein, matching value is equal
Feature related application be ranked up according to correlation is descending；
Sub-step S22-6, according to the sequence, extract predetermined number, matching value corresponds with multiple pre-set intervals
Feature related application, as recommendation application.
When the feature related application that there is identical match value, after calculating matching value and correlation, first according to
Matching value size is ranked up to all of feature related application, for the application of identical match value, enters according to correlation size
Row sequence.Then can choose certain amount matching value and fall in the interval respectively from the several matching values interval set in advance
Interior application recommending, it is same it is interval in, matching value is high to be preferentially selected, and it is high that identical weights then preferentially choose the degree of correlation
's.
For example, 10 feature related applications have been searched, corresponding matching value and correlation are as follows：
| A1 | A2 | B | C | D1 | D2 | E | F | G | H | |
| Matching value | 93 | 93 | 89 | 83 | 57 | 57 | 50 | 49 | 32 | 23 |
| Correlation | 239 | 234 | 2334 | 455 |
Pre-set interval and corresponding predetermined number are：3 [100-88], 2 [87-73], 1 [72-16], according in table
Order C and D1 can be chosen from [87-73] (because the interval only one of which should from [100-88] from A1, A2 and B is chosen
With, then to choose highest from [72-16] interval and supply, D1 with D2 matching values are consistent, but D1 correlations are more than D2, so choosing
D1), E is chosen from 72-16, totally 6 applications are used as recommendation application.
In practice, if according to the user access information and its classification, looked in the application data sets of correspondence classification
The matching application found is unsatisfactory for predetermined number, can extract respective classes application data sets access times it is most and/
Or the application of newest warehouse-in is used as application is recommended, for example, the application data sets of current class extract 20 it is most popular should
It is used as recommending application.
Certainly, above-mentioned lookup matches the method applied with user access information and is solely for example, those skilled in the art
It is also feasible using other computational methods, for example, is answered with respective classes by calculating the subclassification label of user access information
Similarity of subclassification label with data pooled applications etc., the application need not be any limitation as to this.
It should be noted that in the embodiment of the present application, the Main classification label can pass through related to subclassification label
Technical staff or user voluntarily mark, it would however also be possible to employ computer clustering technique, by the semantic or key to webpage word
Word analysis is obtained, can be with from the description information of network (such as official) collection corresponding software or application.
Step 104, each classification corresponding application file folder is generated, it is right that the application of each classification for being found is put into
Recommended in the application file folder answered.
Using the embodiment of the present application, category is generated into application file folder, under respective classes, with user access information
The application matched somebody with somebody is recommended in the application file folder of correspondence classification to user, so as to be conducive to saving the money of user equipment
Source.
With reference to Fig. 2, flow chart the step of it illustrates the embodiment of the method that a kind of application of the application recommends automatically, specifically
May include steps of：
Step 201, collection user access information；
The classification that step 202, the division user access information are belonged to；
Step 203, according to the user access information and its classification, look in the application data sets of preset corresponding classification
Look for the application of matching；
Step 204, each classification corresponding application file folder is generated, it is right that the application of each classification for being found is put into
Recommended in the application file folder answered；
Step 205, the operation frequency for obtaining each applicating category correspondence Main classification label, according to the operation frequency from height
Arrange application file folder represents order；
Step 206, represent application file folder on the desktop of user equipment by the order that represents；
Recommend the weight applied in step 207, acquisition application file folder, in each application file folder, by the power of application
Weight represents from high to low the application.
In implementing, for the application file for recommending user is pressed from both sides, can be opened up in the different split screens of desktop
It is existing, it is preferred that can to determine that the application file recommended in each split screen is pressed from both sides individual with the height of foundation user's split screen and width
Number.Using the embodiment of the present application, the order that represents of the application file folder is according to each applicating category correspondence Main classification label
The operation frequency is arranged from high to low, therefore application file folder is to be presented to use from high to low according to the matching degree of user interest
Family；Also, the application in application file folder is also sorted by weight, that is, be also according to the matching degree of user interest from height to
It is low to be presented to user, so as to be more convenient the operation of user, make user obtain more preferable experience.
In a preferred embodiment of the present application, can also comprise the steps：
User is obtained for the operation information for recommending to apply, the weight of correspondence application is accordingly adjusted.
After recommending to apply to user, user may open the application, check details, it is also possible to further will
The application of recommendation is added in the use of oneself, in this case it is also possible to be believed for the access for recommending application according to user
Breath, improves the weight of the operated application of user, so as to change the sequence applied during application file is pressed from both sides.
In implementing, can also pass through to obtain operation information of the user for application file folder, such as according to user
The operation frequency of application file folder is clicked on, representing for application file folder is accordingly adjusted according to the frequency of each application file double-layered quilt operation
Sequentially.
In implementing, displaying can be unified in the user interface of terminal desktop corresponding with multiple application files folder
Icon, each icon represents application file folder, icon as with using entrance by way of.This patterned exhibition
Show that mode is very directly perceived for a user, and be easy to use and manage.For example, application file folder is shown in user interface
Icon includes " video ", " novel ", " education " and " game ", after the icon that user clicks on " video " application file folder, enters
The subwindow of the application file folder, shows there are multiple application icons such as TV play, film, animation, variety in subwindow.Pass through
Icon can point out user the use to the application as the mode using entrance, but before user really selects use, and
Not actual installation this apply corresponding configuration file, so, not only can be user-friendly, and using front and only
It is take client resource more.
Icon in user interface can concentrate deployment or push by network side central server, This prevents malice journey
Sequence arbitrarily adds malice icon in interface, further increases security.There is the configuration file that central server is managed concentratedly
The reference address of correspondence application can be included, specification, and the unfolding mode of the application, or any combination of them is presented.
For example, for web applications, the address that web is accessed is sent by central server by way of configuration file
To end side, the rogue program that This prevents end side is distorted to reference address.
And, network side central server can be by obtaining the configuration for updating text with interacting for third party content server
Part information, for example, if reference address of certain application changes, server can be by interacting acquisition with content server
Address information after renewal, and sended over by configuration file, prevent because reference address changes what is stayed to rogue program
Opportunity.
Additionally, user equipment can also update the figure after the configuration file for obtaining the application corresponding with the icon
Target display state, further to point out user.For example, do not obtain before configuration file, icon can be black and white, or it is dark-coloured,
And after acquisition, colored or light tone can be changed into.
It should be noted that, can be one or more in application file clip icon shown in the user interface of end side,
Can be determined according to different displaying rules.For example, when using an icon, the icon can be applied as multiple subordinates
Or the unified entrance of subordinate's icon, when one application of any of which obtains fresh information, can obtain at the entrance icon
Prompting.
In a preferred embodiment of the present application, can also comprise the steps：
User access information according to being gathered sets up user characteristics storehouse；
By user for the operation information for recommending to apply, the user characteristics storehouse is write.
By setting up user characteristics storehouse, then user access information can be unified in server end or high in the clouds is processed,
In such an embodiment, user will can be recorded in user characteristics storehouse when secondary operational access information, and according to user characteristics
The previous operational access information in storehouse determines the application file folder and corresponding application that should recommend to user.It should be noted that
In the present embodiment, the user access information also includes user for recommending the operation information of application.
It should be noted that for embodiment of the method, in order to be briefly described, therefore it to be all expressed as a series of action group
Close, but those skilled in the art should know, and the application is not limited by described sequence of movement, because according to this Shen
Please, some steps can adopt other orders or while carry out.Secondly, those skilled in the art also should know, specification
Described in embodiment belong to preferred embodiment, necessary to involved action and module not necessarily the application.
With reference to Fig. 3, the structured flowchart of the device embodiment that a kind of application of the application is recommended automatically is shown, specifically can be with
Including such as lower module：
User accesses acquisition module 301, for gathering user access information；
User's access level division module 302, for dividing the classification that the user access information is belonged to；
Searching modul 303 is applied in matching, for according to the user access information and its classification, in preset corresponding classification
Application data sets search matching application；
Recommending module 304 is applied in matching, for generating each classification corresponding application file folder, by found each
The application of classification is put in corresponding application file folder to be recommended.
In implementing, the user access information can include the local operation access information of user, and/or, use
The online operational access information at family.
In a preferred embodiment of the present application, user's access level division module 302 can include following son
Module：
Feature information extraction submodule, for extracting the user access information in Main classification label and corresponding operation
The frequency；
Classification correspondence submodule, for the Main classification label to be converted to into corresponding application class by default correlation rule
Not；The transformation rule of tag along sort and applicating category based on the default correlation rule；
Sorting sub-module, for counting the operation frequency of each applicating category correspondence Main classification label, each applicating category is pressed
The operation frequency for being counted is ranked up from high to low；
Sort out submodule, for extracting the front n applicating category of predetermined number, belonged to by active user's access information
Classification；Wherein, the n is the positive integer more than 1.
Used as a kind of example of the embodiment of the present application concrete application, the application of the application data sets has Main classification mark
Sign and at least one-level subclassification label, various types of other application data set is respectively by the application group with same Main classification label
Into；In this case, the matching may further include following sub-step using searching modul 303：
Application data set determination sub-module, the classification for being belonged to according to the user access information determines correspondence classification
Application data set；
Tag extraction submodule, for extracting the subclassification label of the user access information；
Tag match submodule, in the application data sets of the correspondence classification, using the user access information
Subclassification label matched with the subclassification label of corresponding level of application, obtain the application of matching and corresponding weight；
Using submodule is chosen, for choosing front m application answering as current class from high to low according to the weight
With in data set match application, wherein, the m is the positive integer more than 1.
Preferably, the weight can include：Matching value between subclassification label, or, between subclassification label
Matching value and application correlation.
In a preferred embodiment of the present application, described device embodiment can also be included such as lower module：
Application file folder sequence display module, for by the operation frequency of each applicating category correspondence Main classification label, arranging
What application file was pressed from both sides represents order；And represent the application file folder on the desktop of user equipment by the order that represents；
Using sequence display module, in each application file folder, by the weight of application described answering being represented from high to low
With.
It is further preferred that described device embodiment can also be included such as lower module：
Weight adjusting module, for obtaining user for the operation information for recommending to apply, accordingly adjusts correspondence application
Weight.
It is further preferred that described device embodiment can also be included such as lower module：
Application file folder order adjusting module, for obtaining operation information of the user for application file folder, corresponding adjustment
What application file was pressed from both sides represents order.
It is further preferred that described device embodiment can also be included such as lower module：
Feature database sets up module, for setting up user characteristics storehouse according to the user access information for being gathered；
Feature database writing module, for the operation information for recommending to apply, the user characteristics storehouse is write for by user.
The embodiment of the present application can be applied not only in the applied environment of single device, can also be applied to server-visitor
The applied environment at family end, or further apply in the applied environment based on cloud.
Because described device embodiment essentially corresponds to preceding method embodiment, thus in the description of the present embodiment it is not detailed it
Place, may refer to the related description in previous embodiment, and here is not just repeated.The application device embodiment and system embodiment
In involved module, submodule and unit can be software, can be hardware, or the combination of software and hardware.This
What each embodiment in specification was stressed is all the difference with other embodiment, phase homophase between each embodiment
As part mutually referring to.
The application can be used in numerous general or special purpose computing system environments or configuration.For example：Personal computer, service
Device computer, handheld device or portable set, laptop device, multicomputer system, based on the system of microprocessor, top set
Box, programmable consumer-elcetronics devices, network PC, minicom, mainframe computer, including any of the above system or equipment
DCE etc..
The application can be described in the general context of computer executable instructions, such as program
Module.Usually, program module includes execution particular task or realizes routine, program, object, the group of particular abstract data type
Part, data structure etc..The application can also be in a distributed computing environment put into practice, in these DCEs, by
The remote processing devices connected by communication network are performing task.In a distributed computing environment, program module can be with
In local and remote computer-readable storage medium including including storage device.
The device that a kind of method and application recommended automatically a kind of application provided herein above is recommended automatically enters
Go and be discussed in detail, specific case used herein has been set forth to the principle and embodiment of the application, the above has been implemented
The explanation of example is only intended to help and understands the present processes and its core concept；Simultaneously for the general technology people of this area
Member, according to the thought of the application, will change in specific embodiments and applications, in sum, this explanation
Book content should not be construed as the restriction to the application.
Claims (16)
1. a kind of method that application is recommended automatically, it is characterised in that include：
Collection user access information；
Divide the classification that the user access information is belonged to；
According to the user access information and its classification, in the application data sets of preset corresponding classification answering for matching is searched
With；
The corresponding application file folder of each classification is generated, the application of each classification for being found is put into into corresponding application file
Recommended in folder；
Wherein, the step of classification that the division user access information is belonged to, includes：
Extract the Main classification label and the corresponding operation frequency in the user access information；
The Main classification label is converted to into corresponding applicating category by default correlation rule；The default correlation rule is
The transformation rule of Main classification label and applicating category；
The operation frequency of each applicating category correspondence Main classification label is counted, by each applicating category by the operation frequency for being counted from height
It is ranked up to low；
Extract the front n applicating category of predetermined number, the classification belonged to by active user's access information；Wherein, the n is big
In 1 positive integer；
If the quantity of the applicating category is unable to reach front n of predetermined number, the network user's reality counted according to high in the clouds
The most applicating category of border access times or most newly-installed applicating category carry out polishing as the applicating category recommended.
2. the method for claim 1, it is characterised in that the user access information includes that the local operation of user is accessed
Information, and/or, the online operational access information of user.
3. the method for claim 1, it is characterised in that the application of the application data sets have Main classification label and
At least one-level subclassification label, various types of other application data set is made up of respectively the application with same Main classification label；
The foundation user access information and its classification, in the application data sets of preset corresponding classification the application of matching is searched
The step of further include：
The classification belonged to according to the user access information determines the application data set of correspondence classification；
Extract the subclassification label of the user access information；
In the application data sets of the correspondence classification, the subclassification label using the user access information is corresponding with application
The subclassification label of rank is matched, and obtains the application of matching and corresponding weight；
The application that front m application is matched as the application data sets of current class is chosen from high to low according to the weight, its
In, the m is the positive integer more than 1.
4. method as claimed in claim 3, it is characterised in that the weight includes：Matching value between subclassification label, or
Person, the correlation of matching value and application between subclassification label.
5. the method for claim 1, it is characterised in that also include：
By the operation frequency of each applicating category correspondence Main classification label, arrange application file folder represents order；
Represent the application file folder on the desktop of user equipment by the order that represents；
In each application file folder, by the weight of application the application is represented from high to low.
6. the method as described in claim 3 or 4 or 5, it is characterised in that also include：
User is obtained for the operation information for recommending to apply, the weight of correspondence application is accordingly adjusted.
7. the method as described in claim 3 or 4 or 5, it is characterised in that also include：
Operation information of the user for application file folder is obtained, accordingly adjust application file folder represents order.
8. the method for claim 1, it is characterised in that also include：
User access information according to being gathered sets up user characteristics storehouse；
By user for the operation information for recommending to apply, the user characteristics storehouse is write.
9. the device that a kind of application is recommended automatically, it is characterised in that include：
User accesses acquisition module, for gathering user access information；
User's access level division module, for dividing the classification that the user access information is belonged to；
Searching modul is applied in matching, for according to the user access information and its classification, in the application of preset corresponding classification
The application of matching is searched in data set；
Recommending module is applied in matching, for generating the corresponding application file folder of each classification, by each classification for being found
Recommended using being put in corresponding application file folder；
Wherein, user's access level division module includes：
Feature information extraction submodule, for extracting the user access information in Main classification label and corresponding operation frequency
It is secondary；
Classification correspondence submodule, for the Main classification label to be converted to into corresponding applicating category by default correlation rule；
The transformation rule of tag along sort and applicating category based on the default correlation rule；
Sorting sub-module, for counting the operation frequency of each applicating category correspondence Main classification label, by each applicating category by being united
The operation frequency of meter is ranked up from high to low；
Sort out submodule, for extracting the front n applicating category of predetermined number, the class belonged to by active user's access information
Not；Wherein, the n is the positive integer more than 1；
If the quantity that the classification submodule is additionally operable to the applicating category is unable to reach front n of predetermined number, according to cloud
The most applicating category of the counted actually used number of times of the network user in end or most newly-installed applicating category should as what is recommended
Polishing is carried out with classification.
10. device as claimed in claim 9, it is characterised in that the user access information includes that the local operation of user is visited
Information is asked, and/or, the online operational access information of user.
11. devices as claimed in claim 9, it is characterised in that the application of the application data sets has Main classification label
At least one-level subclassification label, various types of other application data set is made up of respectively the application with same Main classification label；
The matching is further included using searching modul：
Application data set determination sub-module, the classification for being belonged to according to the user access information determines answering for correspondence classification
Use data set；
Tag extraction submodule, for extracting the subclassification label of the user access information；
Tag match submodule, in the application data sets of the correspondence classification, using the son of the user access information
Tag along sort is matched with the subclassification label of the corresponding level of application, obtains the application of matching and corresponding weight；
Using submodule is chosen, for choosing front m application from high to low as the application number of current class according to the weight
According to the application for concentrating matching, wherein, the m is the positive integer more than 1.
12. devices as claimed in claim 11, it is characterised in that the weight includes：Matching value between subclassification label,
Or, the correlation of matching value and application between subclassification label.
13. devices as claimed in claim 9, it is characterised in that also include：
Application file folder sequence display module, for by the operation frequency of each applicating category correspondence Main classification label, arranging application
File represent order；And represent the application file folder on the desktop of user equipment by the order that represents；
Using sequence display module, in each application file folder, by the weight of application the application being represented from high to low.
14. devices as described in claim 11 or 12 or 13, it is characterised in that also include：
Weight adjusting module, for obtaining user for the operation information for recommending to apply, accordingly adjusts the weight of correspondence application.
15. devices as described in claim 11 or 12 or 13, it is characterised in that also include：
Application file folder order adjusting module, for obtaining operation information of the user for application file folder, corresponding adjustment application
File represent order.
16. devices as claimed in claim 9, it is characterised in that also include：
Feature database sets up module, for setting up user characteristics storehouse according to the user access information for being gathered；
Feature database writing module, for the operation information for recommending to apply, the user characteristics storehouse is write for by user.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201310462445.7A CN103744849B (en) | 2011-12-27 | 2011-12-27 | Method and device for automatic recommendation application |
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201310462445.7A CN103744849B (en) | 2011-12-27 | 2011-12-27 | Method and device for automatic recommendation application |
| CN2011104440740A CN102591942B (en) | 2011-12-27 | 2011-12-27 | Method and device for automatic application recommendation |
Related Parent Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN2011104440740A Division CN102591942B (en) | 2011-12-27 | 2011-12-27 | Method and device for automatic application recommendation |
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| Publication Number | Publication Date |
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| CN103744849A CN103744849A (en) | 2014-04-23 |
| CN103744849B true CN103744849B (en) | 2017-04-12 |
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| CN201310462445.7A Expired - Fee Related CN103744849B (en) | 2011-12-27 | 2011-12-27 | Method and device for automatic recommendation application |
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| CN105916054A (en) * | 2015-10-23 | 2016-08-31 | 乐视致新电子科技（天津）有限公司 | Desktop display control method and device |
| CN105653655A (en) * | 2015-12-25 | 2016-06-08 | Tcl集团股份有限公司 | Application pushing method and device |
| CN105824923A (en) * | 2016-03-17 | 2016-08-03 | 海信集团有限公司 | Movie and video resource recommendation method and device |
| CN106326369B (en) * | 2016-08-12 | 2019-12-31 | 广州优视网络科技有限公司 | Application topic recommendation method and device and server |
| CN106792175A (en) * | 2016-12-22 | 2017-05-31 | 深圳Tcl数字技术有限公司 | Program data processing method and system |
| CN109145280B (en) * | 2017-06-15 | 2023-05-12 | 北京京东尚科信息技术有限公司 | Information pushing method and device |
| CN109213413A (en) * | 2017-07-07 | 2019-01-15 | 阿里巴巴集团控股有限公司 | A kind of recommended method, device, equipment and storage medium |
| CN108428189B (en) * | 2018-02-27 | 2021-04-02 | 上海掌门科技有限公司 | Social resource processing method and device and readable medium |
| CN110555157B (en) * | 2018-03-27 | 2023-04-07 | 阿里巴巴（中国）有限公司 | Content recommendation method, content recommendation device and electronic equipment |
| CN110555131B (en) * | 2018-03-27 | 2023-04-07 | 阿里巴巴（中国）有限公司 | Content recommendation method, content recommendation device and electronic equipment |
| CN110555135B (en) * | 2018-03-27 | 2023-04-07 | 阿里巴巴（中国）有限公司 | Content recommendation method, content recommendation device and electronic equipment |
| CN110766493B (en) * | 2018-07-26 | 2023-04-28 | 阿里巴巴集团控股有限公司 | Service object providing method, server, electronic device, and storage medium |
| CN109325003B (en) * | 2018-09-27 | 2021-09-24 | 维沃移动通信有限公司 | Application program classification method and system based on terminal equipment |
| CN109831532B (en) * | 2019-03-18 | 2020-09-15 | 北京字节跳动网络技术有限公司 | Data sharing method, device, equipment and medium |
| CN110069320B (en) * | 2019-04-29 | 2023-06-30 | 努比亚技术有限公司 | Classification correction method, terminal, system and storage medium for application program |
| CN110333818A (en) * | 2019-05-24 | 2019-10-15 | 华为技术有限公司 | Processing method, device, equipment and the storage medium of split screen display available |
| WO2021217470A1 (en) * | 2020-04-29 | 2021-11-04 | Citrix Systems, Inc. | Computer resource allocation based on categorizing computing processes |
| CN111858688A (en) * | 2020-07-20 | 2020-10-30 | 海尔优家智能科技（北京）有限公司 | Textile material, color chart recommendation method and device and storage medium |
| CN112684953A (en) * | 2020-12-24 | 2021-04-20 | 方正株式(武汉)科技开发有限公司 | Mobile terminal application icon arrangement method |
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