CN102880501A - Realizing method, device and system for recommending applications - Google Patents
Realizing method, device and system for recommending applications Download PDFInfo
- Publication number
- CN102880501A CN102880501A CN2012102588131A CN201210258813A CN102880501A CN 102880501 A CN102880501 A CN 102880501A CN 2012102588131 A CN2012102588131 A CN 2012102588131A CN 201210258813 A CN201210258813 A CN 201210258813A CN 102880501 A CN102880501 A CN 102880501A
- Authority
- CN
- China
- Prior art keywords
- application
- premises access
- ustomer premises
- access equipment
- characteristic
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Landscapes
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The invention discloses a realizing method, a realizing device and a realizing system for recommending applications. The method includes the following steps: unitization processing the characteristic information of applications, so as to obtain the quality scores of the applications, and determining the correlativity of multiple applications according to the historical behavior data of multiple users; and in case that the information of the application recommended to the user needs to be transmitted to the user, other applications can be wholly or partially recommended to the user according to the quality scores of the other applications and the correlativity between the other applications and the object application, and the object application includes the application used at present or before. According to the realizing method, device and system, the applications can be recommended to the user by referring to the characteristics of the applications, therefore, the newly uploaded or little-user operation applications can be reasonably recommended to the user, the inaccuracy of the subjective judgment in recommending the applications can be overcome, and by combining with the relevance to recommend on the basis, the accuracy in recommending can be further improved, and the user experiencing can be improved.
Description
Technical field
The present invention relates to computer communication field, and especially, relate to implementation method, device and system that a kind of application is recommended.
Background technology
Along with the development of intelligent terminal, at present, the intelligent terminal device of a variety of height (herein also referred to as ustomer premises access equipment) has appearred, for example, smart mobile phone, panel computer etc.
Because intelligent terminal has powerful function, therefore, for intelligent terminal, a variety of application (application programs has been proposed, English name is applicant, referred to as app), thus intelligent terminal is carried out further perfect, make intelligent terminal there is more abundant, practical function, effectively improve the user and experience.
At present, there is a large amount of application to sign in on each categorles terminal platform.But, because number of applications is very large, newly-increased application is very many, therefore, how intelligently application to be recommended to the terminal user, avoid the user to carry out a large amount of search and searching work, be a comparatively crucial problem.
At present, although can carry out record by daily record to user's operation, and, can also exist certain similarly application to recommend the user type or scoring.
But currently used suggested design is merely able to record to be recommended according to user's historical operation, therefore, or the application of newly reaching the standard grade less for user's operational ton, be difficult to find comparatively reasonably reference, can't effectively these application be recommended to the user.
For in correlation technique, various application all being recommended to user's problem with reasonable manner, effective solution is not yet proposed at present.
Summary of the invention
For in correlation technique, various application all being recommended to user's problem with reasonable manner, the present invention proposes implementation method, device and the system that a kind of application is recommended, and can various types of application be recommended to ustomer premises access equipment with reasonable manner.
Technical scheme of the present invention is achieved in that
According to an aspect of the present invention, the implementation method that provides a kind of application to recommend.
The method comprises: the characteristic information for application carries out normalized, obtains the massfraction of this application, and determines the degree of association between a plurality of application according to the historical behavior data of a plurality of ustomer premises access equipments; In the situation that recommending the information of the application of ustomer premises access equipment, needs send to ustomer premises access equipment, according to the massfraction of other application and the degree of association between other application and intended application, to in other application, partly or entirely recommend ustomer premises access equipment, wherein, intended application comprise ustomer premises access equipment current or before the operation application.
In addition, in the situation that ustomer premises access equipment is initiated request, the sign of ustomer premises access equipment is determined in the request of initiating by ustomer premises access equipment, and determines the ustomer premises access equipment application of operation before according to sign.
In addition, determine that according to the historical behavior data of a plurality of ustomer premises access equipments the degree of association between a plurality of application comprises:
When the degree of association of determining between the first application and the second application, according to the quantity of the quantity of the quantity to the first application and the second ustomer premises access equipment of all being operated of application, ustomer premises access equipment that the first application is operated and ustomer premises access equipment that the second application is operated, determine the degree of association of the first application between applying with second.
And, for each application, the characteristic information of this application comprises a plurality of characteristic parameters, and, the massfraction that obtains this application comprises: the data to a plurality of characteristic parameters of this application are carried out normalized, by the data-mapping after normalized, are signature identification and characteristic of correspondence value; Obtain training data according to a plurality of characteristic parameter characteristic of correspondence values; Obtain the massfraction of this application according to training data and predetermined training pattern.
And, the characteristic information of one application is carried out to normalized further to be comprised: before carrying out normalized, the characteristic parameter that is successive value for value, carry out the characteristic parameter after smoothing processing obtains smoothly according to the maximal value of the current minimum value until level and smooth serial number, current smoothed data and current smoothed data to this characteristic information.
And, a plurality of characteristic parameters comprise following one of at least: the time span that the number of times that is opened of the download of this application, the entry time of this application, this application, the unloaded number of times of this application, this application are used, ustomer premises access equipment are to the scoring of this application, the title of this application, the title of this application institute corresponding label.
In addition, the ustomer premises access equipment of partly or entirely recommending in other application is comprised:
Each application in other application, be weighted summation to the massfraction of this application and the similarity between this application and intended application, obtains the recommendation scores of this application; Ustomer premises access equipment is recommended in the application that recommendation scores in other application is reached to the predetermined score value.
According to a further aspect in the invention, the implement device that provides a kind of application to recommend.
This device comprises: the normalized module, carry out normalized for the characteristic information to application, and obtain the massfraction of each application; Determination module, determine the degree of association between a plurality of application for the historical behavior data according to a plurality of ustomer premises access equipments; The recommendation process module, for in the situation that needs will be recommended the information of the application of ustomer premises access equipment, sending to ustomer premises access equipment, according to the massfraction of other application and the degree of association between other application and intended application, to in other application, partly or entirely recommend ustomer premises access equipment, wherein, intended application comprise ustomer premises access equipment current or before the operation application.
Wherein, when the degree of association of determining between the first application and the second application, determination module is for the quantity of the quantity of the quantity according to the first application and the second ustomer premises access equipment of all being operated of application, ustomer premises access equipment that the first application is operated and ustomer premises access equipment that the second application is operated, determines the degree of association of the first application between applying with second.
In addition, for each application, the characteristic information of this application comprises a plurality of characteristic parameters, and, the normalization module is carried out normalized for the data of a plurality of characteristic parameters to this application, by the data-mapping after normalized, is signature identification and characteristic of correspondence value; The normalization module is also for obtaining training data according to a plurality of characteristic parameter characteristic of correspondence values; And, also for obtain the massfraction of this application according to training data and predetermined training pattern.
In addition, the characteristic parameter that is successive value for value, the normalized module, also for before carrying out normalized, is carried out the characteristic parameter after smoothing processing obtains smoothly according to the maximal value of the current minimum value until level and smooth serial number, current smoothed data and current smoothed data to this characteristic information.
Preferably, a plurality of characteristic parameters comprise following one of at least: the time span that the number of times that is opened of the download of this application, the entry time of this application, this application, the unloaded number of times of this application, this application are used, ustomer premises access equipment are to the scoring of this application, the title of this application, the title of this application institute corresponding label.
In addition, for each application in other application, the recommendation process module, for the massfraction of this application and the similarity between this application and intended application are weighted to summation, obtains the recommendation scores of this application; And the recommendation process module is recommended ustomer premises access equipment for the application that other application recommendation scores are reached to the predetermined score value.
According on the one hand of the present invention, the system that realizes that provides a kind of application to recommend.
This system comprises: log unit for obtaining the historical behavior data of a plurality of ustomer premises access equipments, and sends to recommendation unit by the historical behavior data of obtaining; Placement unit, for capturing the characteristic information of application, and send to recommendation unit by the characteristic information of crawl; Recommendation unit comprises: the normalized module, carry out normalized for the characteristic information to application, and obtain the massfraction of each application; Determination module, determine the degree of association between a plurality of application for the historical behavior data according to a plurality of ustomer premises access equipments; The recommendation process module, for in the situation that needs will be recommended the information of the application of ustomer premises access equipment, sending to ustomer premises access equipment, according to the massfraction of other application and the degree of association between other application and intended application, to in other application, partly or entirely recommend ustomer premises access equipment, wherein, intended application comprise ustomer premises access equipment current or before the operation application.
The present invention is by carrying out to application the massfraction that normalized is applied, and according to the association between application, thereby using, this recommends ustomer premises access equipment as foundation by application, can application be recommended to ustomer premises access equipment with reference to the feature of application itself, therefore, for the application of just reaching the standard grade or the ustomer premises access equipment operational ton is less, also can reasonably recommend ustomer premises access equipment, and the inaccuracy of subjective judgement in the time of can overcoming exemplary application, and, in conjunction with relevance, recommended on this basis, can further improve the accuracy of recommendation, improving the user experiences.
The accompanying drawing explanation
In order to be illustrated more clearly in the embodiment of the present invention or technical scheme of the prior art, below will the accompanying drawing of required use in embodiment be briefly described, apparently, accompanying drawing in the following describes is only some embodiments of the present invention, for those of ordinary skills, under the prerequisite of not paying creative work, can also obtain according to these accompanying drawings other accompanying drawing.
Fig. 1 is the process flow diagram according to the implementation method of the application recommendation of the embodiment of the present invention;
Fig. 2 is the principle schematic according to the implementation method of the application recommendation of the embodiment of the present invention;
Fig. 3 is the block diagram according to the implement device of the application recommendation of the embodiment of the present invention;
Fig. 4 is the block diagram according to the system that realizes of the application recommendation of the embodiment of the present invention.
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is clearly and completely described, obviously, described embodiment is only the present invention's part embodiment, rather than whole embodiment.Embodiment based in the present invention, the every other embodiment that those of ordinary skills obtain, belong to the scope of protection of the invention.
According to embodiments of the invention, the implementation method that provides a kind of application to recommend.The ustomer premises access equipment of hereinafter mentioning can refer to user terminal, namely usually said user.In addition, the ustomer premises access equipment of mentioning herein can be not only mobile phone terminal, can be also the multiple terminal equipment such as notebook computer, panel computer, computer equipment, personal digital assistant (PDA).In addition, the application mentioned herein (, application program, English name is applicant, referred to as app), can be the application program that can be applied to several operation systems, these operating systems include but not limited to the multiple operating systems that are applicable to ustomer premises access equipment such as windows, iOS, Android (Android), Symbian (Saipan).
The implementation method of recommending according to the application of the embodiment of the present invention as shown in Figure 1, comprises:
Step S101, characteristic information for application carries out normalized, obtain the massfraction of this application (wherein, the massfraction here is the feature of application itself and/or a kind of embodiment of applying current service condition), and determine the degree of association between a plurality of application according to the historical behavior data of a plurality of ustomer premises access equipments;
Wherein, the purpose of normalized is that dissimilar parameter is carried out to unified quantization, obtain the numerical value of this parameter, thereby make these parameters can be calculated each other, its purpose is to obtain by means of each characteristic information of each application the quality of this application, thereby makes massfraction can react more objectively all features of this application.
Step S103, in the situation that recommending the information of the application of ustomer premises access equipment, needs send to ustomer premises access equipment, according to the massfraction of other application and the degree of association between other application and intended application, to in other application, partly or entirely recommend ustomer premises access equipment, wherein, intended application comprises the application of the current or operation before of ustomer premises access equipment (the operation here can comprise browse, comment on, download, install, operation or its combination such as unloading).
Wherein, can be in the situation that ustomer premises access equipment to be initiated request, the sign of ustomer premises access equipment is determined in the request of initiating by ustomer premises access equipment, and determines the ustomer premises access equipment application of operation before according to sign.
In addition, when the degree of association of determining between the first application and the second application, according to the quantity of the quantity of the quantity to the first application and the second ustomer premises access equipment of all being operated of application, ustomer premises access equipment that the first application is operated and ustomer premises access equipment that the second application is operated, determine the degree of association of the first application between applying with second.
Particularly, when the historical behavior data according to a plurality of ustomer premises access equipments are determined the degree of association between a plurality of application, for application A and application B, according to following formula, determine the degree of association sim (A, B) between these two application:
Wherein, count (A, B) clicks application A simultaneously, the ustomer premises access equipment number of B, and count (A) is the ustomer premises access equipment number of clicking application A, count (B) is the ustomer premises access equipment number of clicking application B.
In addition, for each application, the characteristic information of this application comprises a plurality of characteristic parameters, and, when obtaining the massfraction of this application, can carry out normalized to the data of a plurality of characteristic parameters of this application, be signature identification and characteristic of correspondence value by the data-mapping after normalized; Obtain training data according to a plurality of characteristic parameter characteristic of correspondence values; Obtain the massfraction of this application according to training data and predetermined training pattern.
Alternatively, before carrying out normalized, the characteristic parameter that is successive value for value, carry out the characteristic parameter after smoothing processing obtains smoothly according to the maximal value of the current minimum value until level and smooth serial number, current smoothed data and current smoothed data to this characteristic information.
Particularly, can carry out the characteristic parameter f (score) after smoothing processing obtains smoothly according to following formula to this characteristic information in advance:
Wherein, score is the current level and smooth serial number for the treatment of, minScore is the minimum value of current smoothed data, and maxScore is the maximal value of current smoothed data.
Alternatively, for each application, for a plurality of characteristic parameters of calculated mass mark can comprise following one of at least: the time span that the number of times that is opened of the download of this application, the entry time of this application, this application, the unloaded number of times of this application, this application are used, ustomer premises access equipment are to the scoring of this application, the title of this application, the title of this application institute corresponding label.
It should be noted that to be only concrete example for enumerating of characteristic parameter here.In actual applications, the parameter that can select other is as the foundation of carrying out massfraction calculating.
In addition, in said method, by other the application in partly or entirely recommend ustomer premises access equipment the time, for other the application in each application, the massfraction of this application and the similarity between this application and intended application are weighted to summation, obtain the recommendation scores of this application.
Particularly, can determine according to following formula the recommendation scores of this application:
F (score)=α * simScore+ (1-α) * qualityScore; Wherein, α is value 0-1 number, and simScore means the similarity of this application and intended application, and qualityScore means the massfraction of this application; Ustomer premises access equipment is recommended in the application that recommendation scores in other application is reached to the predetermined score value.
Fig. 2 is the schematic diagram according to the concrete implementation of the said method of the embodiment of the present invention.
As shown in Figure 2, wherein specifically comprise the following steps:
(step 1) ustomer premises access equipment behavioral data obtains
The user behavior acquisition module is mainly to obtain the user initiatively to click behavior, is the basis of proposed algorithm operation.When the user clicks a application, program can send the log daily record automatically to log server.Log server gathers daily record, and Timing Synchronization, to the hadoop cluster, for follow-up recommendation, also just in this way, can be known the application that the user is current or operated before.
The log got ready on server at least comprises following field: ustomer premises access equipment sign, application identities, the fields such as time that ustomer premises access equipment is clicked.
(step 2) takes the correlation recommendation algorithm, according to the similarity between the behavioral data computing application of ustomer premises access equipment.Similarity data between being applied.
According to the access history of all ustomer premises access equipments, according to calculating formula of similarity, the similarity between computing application.The similarity formula is as follows:
Wherein, count (A, B) clicks application A, the ustomer premises access equipment number of B simultaneously.
Count (A) is the ustomer premises access equipment number of clicking application A.
Count (B) is the ustomer premises access equipment number of clicking application B.
(step 3) according to above result of calculation, the similarity data (relevance) of be applied (item).
(step 4) obtains the various data for the computing application quality assessment, comprises download, entry time, opens number of times, discharging quantity, use duration, the scoring of ustomer premises access equipment, Apply Names, application tag.
(step 5) by the data normalization of each feature, and is mapped to feature id, calculates mark the training pattern of each feature.
Particularly, in step 5, for value, be continuous data, at first by numerical value normalization and smoothing processing, the smoothing formula of taking is as follows:
Wherein score is the current level and smooth serial number for the treatment of, minScore is the minimum value of current smoothed data, and maxScore is the maximal value of current smoothed data.
For the data after level and smooth, the interval according to 0.1 changes into feature by data discrete.For example:
| Feature id | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 |
| Numerical value | 0.1 | 0.2 | 0.3 | 0.4 | 0.5 | 0.6 | 0.7 | 0.8 | 0.9 |
If the numerical value value after level and smooth is 0.25, the value of the 2nd corresponding feature is 1.
Corresponding discrete data, Apply Names for example, the continuous English character each Chinese character and space separated is as a feature.
For example: for application " Show time! Handsome man comes on stage ", characteristic of correspondence has
| Feature id | 551 | 552 | 553 | 554 | 555 | 556 |
| The feature implication | Show | time | Handsome | The man | Step on |
For the every money application in the training array, calculate the clicking rate of each application, if be less than 0.5, target is made as to 0, otherwise target is made as to 1.
Above-mentioned data are input in Logic Regression Models to training pattern.
For example, for " Show time! Handsome man comes on stage " this application, if its download is 100, entry time is 2012-06-05,
Opening number of times is 10 times, and discharging quantity is 5 times, and using duration is 30 minutes, and user's scoring is 5 minutes, and application tag is the life leisure.
At first, the feature number of agreement download is 1 to 100, the feature number of entry time is 101 to 200, the feature number of opening number of times is 201 to 300, the feature number of discharging quantity is from 301 to 400, using the feature number of duration is from 401 to 500, and the feature number of user's scoring is from 501 to 550, and the characteristic interval of Apply Names and tag is 551 to 3000.
Corresponding each above-mentioned feature, carry out normalization according to the normalized method of feature, and for example, if the numerical value after download normalization is 0.25, to be numbered 2 feature value be 1 to feature id.Adopt and use the same method, other successional feature characteristic of correspondence id numberings are set to 1, here, suppose entry time corresponding be 101, open number of times corresponding be 201, discharging quantity characteristic of correspondence id is 301, use duration characteristic of correspondence id is 401.For discontinuous feature, for example, Apply Names, if male characteristic of correspondence id numbering is 554,554 of correspondence value is 1.
By above-mentioned each feature extraction out, final training data is as follows:
2∶1 101∶1 201∶1 301∶1 401∶1 551∶1 552∶1 553∶1 554∶1 554∶1。
The model that (step 6) basis trains is to each computation massfraction.
(step 7) merges massfraction and similarity score, obtains final recommender score.
Calculate final score, main comprehensive similarity mark and quality are divided, and the formula of taking is as follows:
f(score)＝α*simScore+(1-α)*qualityScore
Wherein, α is the number of value 0-1, and simScore means the mark of similarity, and qualityScore means the quality score of application.
(step 8) obtains final recommendation results, and recommendation results is sent to ustomer premises access equipment.
According to embodiments of the invention, the implement device that also provides a kind of application to recommend.
As shown in Figure 3, the implement device of recommending according to the application of the embodiment of the present invention comprises:
Wherein, when the degree of association of determining between the first application and the second application, determination module is for the quantity of the quantity of the quantity according to the first application and the second ustomer premises access equipment of all being operated of application, ustomer premises access equipment that the first application is operated and ustomer premises access equipment that the second application is operated, determines the degree of association of the first application between applying with second.
Particularly, for application A and application B, determination module is for determining the degree of association sim (A, B) between these two application according to following formula:
Wherein, count (A, B) clicks application A simultaneously, the ustomer premises access equipment number of B, and count (A) is the ustomer premises access equipment number of clicking application A, count (B) is the ustomer premises access equipment number of clicking application B.
In addition, for each application, the characteristic information of this application comprises a plurality of characteristic parameters, and, the normalization module is carried out normalized for the data of a plurality of characteristic parameters to this application, by the data-mapping after normalized, is signature identification and characteristic of correspondence value; The normalization module is also for obtaining training data according to a plurality of characteristic parameter characteristic of correspondence values; And, also for obtain the massfraction of this application according to training data and predetermined training pattern.
Alternatively, the characteristic parameter that is successive value for value, the normalized module, also for before carrying out normalized, is carried out the characteristic parameter after smoothing processing obtains smoothly according to the maximal value of the current minimum value until level and smooth serial number, current smoothed data and current smoothed data to this characteristic information.Particularly, can carry out the characteristic parameter f (score) after smoothing processing obtains smoothly to this characteristic information according to following formula:
Wherein, score is the current level and smooth serial number for the treatment of, minScore is the minimum value of current smoothed data, and maxScore is the maximal value of current smoothed data.
Preferably, a plurality of characteristic parameters comprise following one of at least:
The time span that the number of times that is opened of the download of this application, the entry time of this application, this application, the unloaded number of times of this application, this application are used, ustomer premises access equipment are to the scoring of this application, the title of this application, the title of this application institute corresponding label.
In addition, for each application in other application, the recommendation process module, for the massfraction of this application and the similarity between this application and intended application are weighted to summation, obtains the recommendation scores of this application; And the recommendation process module is recommended ustomer premises access equipment for the application that other application recommendation scores are reached to the predetermined score value.Particularly, the recommendation process module is for determining the recommendation scores of this application according to following formula:
F (score)=α * simScore+ (1-α) * qualityScore; Wherein, α is value 0-1 number, and simScore means the similarity of this application and intended application, and qualityScore means the massfraction of this application;
And the recommendation process module is recommended ustomer premises access equipment for the application that other application recommendation scores are reached to the predetermined score value.
According to embodiments of the invention, the system that realizes that also provides a kind of application to recommend.
The system that realizes of recommending according to the application of the embodiment of the present invention as shown in Figure 4, comprises:
Wherein, recommendation unit 43 comprises:
Normalized module (not shown), carry out normalized for the characteristic information to application, obtains the massfraction of each application; The determination module (not shown), determine the degree of association between a plurality of application for the historical behavior data according to a plurality of ustomer premises access equipments; Recommendation process module (not shown), for in the situation that needs will be recommended the information of the application of ustomer premises access equipment, sending to ustomer premises access equipment, according to the massfraction of other application and the degree of association between other application and intended application, to in other application, partly or entirely recommend ustomer premises access equipment, wherein, intended application comprise ustomer premises access equipment current or before the operation application.
In actual applications, each in log unit, recommendation unit and placement unit all can realize by different servers (or server unit), also can realize by the mode of program being arranged in consolidated network equipment.If realize said units by independent server, the server at log unit place can be called log server, and the server at recommendation unit place can be called recommendation server, and the server at placement unit place can be called the crawl server.
System is as shown in Figure 4 carried out work according to following flow process:
In sum, by means of technique scheme of the present invention, by application is carried out to the massfraction that normalized is applied, and according to the association between application, thereby using, this recommends ustomer premises access equipment as foundation by application, can application be recommended to ustomer premises access equipment with reference to the feature of application itself, therefore, for the application of just reaching the standard grade or the ustomer premises access equipment operational ton is less, also can reasonably recommend ustomer premises access equipment, and the inaccuracy of subjective judgement in the time of can overcoming exemplary application, and, in conjunction with relevance, recommended on this basis, can further improve the accuracy of recommendation, improving the user experiences.
The foregoing is only preferred embodiment of the present invention, in order to limit the present invention, within the spirit and principles in the present invention not all, any modification of doing, be equal to replacement, improvement etc., within all should being included in protection scope of the present invention.
Claims (14)
1. apply the implementation method that app recommends for one kind, it is characterized in that, comprising:
Characteristic information for application carries out normalized, obtains the massfraction of this application, and determines the degree of association between a plurality of application according to the historical behavior data of a plurality of ustomer premises access equipments;
In the situation that recommending the information of the application of ustomer premises access equipment, needs send to ustomer premises access equipment, according to the massfraction of other application and the degree of association between other application and intended application, to in other application, partly or entirely recommend ustomer premises access equipment, wherein, described intended application comprise described ustomer premises access equipment current or before the operation application.
2. implementation method according to claim 1, it is characterized in that, in the situation that ustomer premises access equipment is initiated request, the sign of described ustomer premises access equipment is determined in the request of initiating by ustomer premises access equipment, and determines according to described sign the application operated before described ustomer premises access equipment.
3. implementation method according to claim 1, is characterized in that, according to the historical behavior data of a plurality of ustomer premises access equipments, determines that the degree of association between a plurality of application comprises:
When the degree of association of determining between the first application and the second application, according to the quantity of the quantity of the quantity to described the first application and described the second ustomer premises access equipment of all being operated of application, ustomer premises access equipment that described the first application is operated and ustomer premises access equipment that described the second application is operated, determine the degree of association of described the first application and described second between applying.
4. implementation method according to claim 1, is characterized in that, for each application, the characteristic information of this application comprises a plurality of characteristic parameters, and the massfraction that obtains this application comprises:
Data to a plurality of characteristic parameters of this application are carried out normalized, by the data-mapping after normalized, are signature identification and characteristic of correspondence value;
Obtain training data according to described a plurality of characteristic parameter characteristic of correspondence values;
Obtain the massfraction of this application according to described training data and predetermined training pattern.
5. implementation method according to claim 4, is characterized in that, the characteristic information of an application carried out to normalized and further comprise:
Before carrying out normalized, the characteristic parameter that is successive value for value, carry out the characteristic parameter after smoothing processing obtains smoothly according to the maximal value of the current minimum value until level and smooth serial number, current smoothed data and current smoothed data to this characteristic information.
6. according to the described implementation method of claim 4 or 5, it is characterized in that, described a plurality of characteristic parameters comprise following one of at least:
The time span that the number of times that is opened of the download of this application, the entry time of this application, this application, the unloaded number of times of this application, this application are used, ustomer premises access equipment are to the scoring of this application, the title of this application, the title of this application institute corresponding label.
7. implementation method according to claim 1, is characterized in that, the ustomer premises access equipment of partly or entirely recommending in other application is comprised:
Each application in other application, be weighted summation to the massfraction of this application and the similarity between this application and intended application, obtains the recommendation scores of this application;
Described ustomer premises access equipment is recommended in the application that recommendation scores in other application is reached to the predetermined score value.
8. an implement device of applying recommendation, is characterized in that, comprising:
The normalized module, carry out normalized for the characteristic information to application, obtains the massfraction of each application;
Determination module, determine the degree of association between a plurality of application for the historical behavior data according to a plurality of ustomer premises access equipments;
The recommendation process module, for in the situation that needs will be recommended the information of the application of ustomer premises access equipment, sending to ustomer premises access equipment, according to the massfraction of other application and the degree of association between other application and intended application, to in other application, partly or entirely recommend ustomer premises access equipment, wherein, described intended application comprise described ustomer premises access equipment current or before the operation application.
9. implement device according to claim 8, is characterized in that,
When the degree of association of determining between the first application and the second application, described determination module is for the quantity of the quantity of the quantity according to described the first application and described the second ustomer premises access equipment of all being operated of application, ustomer premises access equipment that described the first application is operated and ustomer premises access equipment that described the second application is operated, determines the degree of association of described the first application and described second between applying.
10. implement device according to claim 8, it is characterized in that, for each application, the characteristic information of this application comprises a plurality of characteristic parameters, and, described normalization module is carried out normalized for the data of a plurality of characteristic parameters to this application, by the data-mapping after normalized, is signature identification and characteristic of correspondence value; Described normalization module is also for obtaining training data according to described a plurality of characteristic parameter characteristic of correspondence values; And, also for obtain the massfraction of this application according to described training data and predetermined training pattern.
11. implement device according to claim 10, it is characterized in that, the characteristic parameter that is successive value for value, described normalized module, also for before carrying out normalized, is carried out the characteristic parameter after smoothing processing obtains smoothly according to the maximal value of the current minimum value until level and smooth serial number, current smoothed data and current smoothed data to this characteristic information.
12. according to the described implement device of claim 10 or 11, it is characterized in that, described a plurality of characteristic parameters comprise following one of at least:
The time span that the number of times that is opened of the download of this application, the entry time of this application, this application, the unloaded number of times of this application, this application are used, ustomer premises access equipment are to the scoring of this application, the title of this application, the title of this application institute corresponding label.
13. implement device according to claim 8, it is characterized in that, for each application in other application, described recommendation process module, for the massfraction of this application and the similarity between this application and intended application are weighted to summation, obtains the recommendation scores of this application;
And described recommendation process module is recommended described ustomer premises access equipment for the application that other application recommendation scores are reached to the predetermined score value.
14. the system that realizes of applying recommendation, is characterized in that, comprising:
Log unit, for obtaining the historical behavior data of a plurality of ustomer premises access equipments, and send to recommendation unit by the historical behavior data of obtaining;
Placement unit, for capturing the characteristic information of application, and send to described recommendation unit by the characteristic information of crawl;
Described recommendation unit comprises:
The normalized module, carry out normalized for the characteristic information to application, obtains the massfraction of each application;
Determination module, determine the degree of association between a plurality of application for the historical behavior data according to a plurality of ustomer premises access equipments;
The recommendation process module, for in the situation that needs will be recommended the information of the application of ustomer premises access equipment, sending to ustomer premises access equipment, according to the massfraction of other application and the degree of association between other application and intended application, to in other application, partly or entirely recommend ustomer premises access equipment, wherein, described intended application comprise described ustomer premises access equipment current or before the operation application.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201210258813.1A CN102880501B (en) | 2012-07-24 | 2012-07-24 | Implementation method, device and system that application is recommended |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201210258813.1A CN102880501B (en) | 2012-07-24 | 2012-07-24 | Implementation method, device and system that application is recommended |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN102880501A true CN102880501A (en) | 2013-01-16 |
| CN102880501B CN102880501B (en) | 2016-05-25 |
Family
ID=47481840
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201210258813.1A Active CN102880501B (en) | 2012-07-24 | 2012-07-24 | Implementation method, device and system that application is recommended |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN102880501B (en) |
Cited By (49)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103475644A (en) * | 2013-08-22 | 2013-12-25 | 北京奇虎科技有限公司 | Method and device for pushing network applications |
| CN103544220A (en) * | 2013-09-29 | 2014-01-29 | 北京航空航天大学 | Method and device for recommending applications |
| CN103595758A (en) * | 2013-10-11 | 2014-02-19 | 北京奇虎科技有限公司 | Method and device for recommending software |
| CN103744966A (en) * | 2014-01-07 | 2014-04-23 | Tcl集团股份有限公司 | Item recommendation method and device |
| CN103838884A (en) * | 2014-03-31 | 2014-06-04 | 联想(北京)有限公司 | Information processing equipment and information processing method |
| CN103902729A (en) * | 2014-04-14 | 2014-07-02 | 广州金山网络科技有限公司 | Method and device for recommending application program |
| CN103984692A (en) * | 2013-02-08 | 2014-08-13 | 三星电子株式会社 | Method and device for providing recommendation panel, and method and server for providing recommendation item |
| CN104158865A (en) * | 2014-08-01 | 2014-11-19 | 北京奇虎科技有限公司 | Method and system for pushing applications to terminal |
| CN104182545A (en) * | 2014-09-05 | 2014-12-03 | 北京金山安全软件有限公司 | Application program recommendation method and device |
| CN104270429A (en) * | 2014-09-19 | 2015-01-07 | 北京奇虎科技有限公司 | Method and device for pushing application to terminal |
| CN104518954A (en) * | 2013-09-30 | 2015-04-15 | 腾讯科技（深圳）有限公司 | Method, device and open platform for transmitting information |
| CN104615661A (en) * | 2015-01-05 | 2015-05-13 | 华为技术有限公司 | Service recommendation method, device and system oriented to cloud platform applications |
| CN104852962A (en) * | 2015-04-09 | 2015-08-19 | 乐视致新电子科技（天津）有限公司 | Method, terminal device, server and system for processing focused information |
| CN104991914A (en) * | 2015-06-23 | 2015-10-21 | 腾讯科技（深圳）有限公司 | Application recommendation method and server |
| CN105095305A (en) * | 2014-05-20 | 2015-11-25 | 深圳市腾讯计算机系统有限公司 | Method and device for generating personalized page |
| CN105117440A (en) * | 2015-08-11 | 2015-12-02 | 北京奇虎科技有限公司 | Method and apparatus for determining to-be-recommended application (APP) |
| CN105279079A (en) * | 2014-06-25 | 2016-01-27 | 腾讯科技（深圳）有限公司 | Application performance estimating method, apparatus and system |
| CN105630957A (en) * | 2015-12-24 | 2016-06-01 | 北京大学 | User management application behavior-based application quality distinguishing method and system |
| CN105653343A (en) * | 2016-02-26 | 2016-06-08 | 北京金山安全软件有限公司 | Software display method and device and electronic equipment |
| CN105787053A (en) * | 2016-02-26 | 2016-07-20 | 维沃移动通信有限公司 | Application pushing method and terminal |
| CN106096035A (en) * | 2016-06-23 | 2016-11-09 | 维沃移动通信有限公司 | A kind of recommendation method of application program and mobile terminal |
| WO2016206482A1 (en) * | 2015-06-24 | 2016-12-29 | 腾讯科技（深圳）有限公司 | Service processing method, server, and computer storage medium |
| CN106452808A (en) * | 2015-08-04 | 2017-02-22 | 北京奇虎科技有限公司 | Data processing method and data processing device |
| CN106445971A (en) * | 2015-08-11 | 2017-02-22 | 北京奇虎科技有限公司 | Application recommendation method and system |
| CN106776906A (en) * | 2016-11-30 | 2017-05-31 | 努比亚技术有限公司 | One kind application clustering method and device |
| CN106993038A (en) * | 2017-03-31 | 2017-07-28 | 北京猎豹移动科技有限公司 | Promotion method, device and the server of application program |
| CN107045688A (en) * | 2016-02-05 | 2017-08-15 | 上海行邑信息科技有限公司 | A kind of control method and device of accurate identification target terminal |
| CN107102876A (en) * | 2017-04-26 | 2017-08-29 | 深圳天珑无线科技有限公司 | Application pushing method and device |
| CN107133296A (en) * | 2017-04-26 | 2017-09-05 | 努比亚技术有限公司 | A kind of application program recommends method, device and computer-readable recording medium |
| CN107229734A (en) * | 2017-06-12 | 2017-10-03 | 深圳市乃斯网络科技有限公司 | Terminal app based on positioning recommends method and system |
| CN107292463A (en) * | 2016-03-30 | 2017-10-24 | 阿里巴巴集团控股有限公司 | A kind of method and system that the project evaluation is carried out to application program |
| WO2018010591A1 (en) * | 2016-07-12 | 2018-01-18 | 腾讯科技（深圳）有限公司 | Information push method and apparatus, server, and storage medium |
| CN107644079A (en) * | 2015-05-22 | 2018-01-30 | 广东欧珀移动通信有限公司 | Method and device and related media production are recommended in one kind application |
| CN107735766A (en) * | 2015-06-05 | 2018-02-23 | 苹果公司 | The system and method for providing recommendation for the proactive property of the user to computing device |
| CN107844536A (en) * | 2017-10-18 | 2018-03-27 | 西安万像电子科技有限公司 | The methods, devices and systems of application program selection |
| CN108319449A (en) * | 2017-01-16 | 2018-07-24 | 北京金山云网络技术有限公司 | A kind of application architecture determines method and device |
| CN104166696B (en) * | 2014-08-01 | 2018-07-27 | 小米科技有限责任公司 | Application program method for pushing and device |
| WO2018145577A1 (en) * | 2017-02-08 | 2018-08-16 | 腾讯科技（深圳）有限公司 | Facial-expression recommendation method and device |
| CN108717513A (en) * | 2018-04-27 | 2018-10-30 | 上海爱优威软件开发有限公司 | A kind of information sharing method and system based on terminal operation |
| CN109213799A (en) * | 2017-06-29 | 2019-01-15 | 北京搜狗科技发展有限公司 | A kind of recommended method and device of cell dictionary |
| CN109299349A (en) * | 2018-09-11 | 2019-02-01 | 广州视源电子科技股份有限公司 | Application recommendation method and device, equipment and computer-readable storage medium |
| CN109710850A (en) * | 2018-12-27 | 2019-05-03 | 杭州启迪万华科技产业发展有限公司 | A kind of public platform information association treating method and apparatus |
| CN109710857A (en) * | 2018-12-27 | 2019-05-03 | 杭州启迪万华科技产业发展有限公司 | A kind of public platform recommended method and device |
| CN109872206A (en) * | 2017-12-04 | 2019-06-11 | 北京京东尚科信息技术有限公司 | Assess determination method for parameter, device and computer readable storage medium |
| CN110175290A (en) * | 2019-05-24 | 2019-08-27 | 竞技世界(成都)网络技术有限公司 | A kind of content delivery method and device |
| CN110688582A (en) * | 2019-11-12 | 2020-01-14 | 广东小天才科技有限公司 | Application recommendation method, application recommendation device and terminal equipment |
| CN112328935A (en) * | 2020-10-29 | 2021-02-05 | 胡培培 | Application program pushing system and method based on big data |
| US10943260B2 (en) | 2013-02-08 | 2021-03-09 | Samsung Electronics Co., Ltd. | Method and device for providing recommendation panel, and method and server for providing recommendation item |
| CN108596711B (en) * | 2018-03-28 | 2021-04-23 | 阿里巴巴（中国）有限公司 | Application recommendation method and device and electronic equipment |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| TWI609315B (en) * | 2016-06-03 | 2017-12-21 | 宏碁股份有限公司 | Application recommendation method and electronic device using the same |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101685458A (en) * | 2008-09-27 | 2010-03-31 | 华为技术有限公司 | Recommendation method and system based on collaborative filtering |
| CN102169566A (en) * | 2010-02-26 | 2011-08-31 | 国际商业机器公司 | Method and device for creating recommended items in unfamiliar fields |
| CN102508870A (en) * | 2011-10-10 | 2012-06-20 | 南京大学 | Individualized recommending method in combination of rating data and label data |
| CN102521754A (en) * | 2010-10-18 | 2012-06-27 | 微软公司 | Capability-based application recommendation |
| CN102567511A (en) * | 2011-12-27 | 2012-07-11 | 奇智软件（北京）有限公司 | Method and device for automatically recommending application |
-
2012
- 2012-07-24 CN CN201210258813.1A patent/CN102880501B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101685458A (en) * | 2008-09-27 | 2010-03-31 | 华为技术有限公司 | Recommendation method and system based on collaborative filtering |
| CN102169566A (en) * | 2010-02-26 | 2011-08-31 | 国际商业机器公司 | Method and device for creating recommended items in unfamiliar fields |
| CN102521754A (en) * | 2010-10-18 | 2012-06-27 | 微软公司 | Capability-based application recommendation |
| CN102508870A (en) * | 2011-10-10 | 2012-06-20 | 南京大学 | Individualized recommending method in combination of rating data and label data |
| CN102567511A (en) * | 2011-12-27 | 2012-07-11 | 奇智软件（北京）有限公司 | Method and device for automatically recommending application |
Cited By (71)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103984692A (en) * | 2013-02-08 | 2014-08-13 | 三星电子株式会社 | Method and device for providing recommendation panel, and method and server for providing recommendation item |
| US10943260B2 (en) | 2013-02-08 | 2021-03-09 | Samsung Electronics Co., Ltd. | Method and device for providing recommendation panel, and method and server for providing recommendation item |
| CN103475644A (en) * | 2013-08-22 | 2013-12-25 | 北京奇虎科技有限公司 | Method and device for pushing network applications |
| CN103475644B (en) * | 2013-08-22 | 2016-08-24 | 北京奇虎科技有限公司 | The method for pushing of a kind of network application and device |
| CN103544220A (en) * | 2013-09-29 | 2014-01-29 | 北京航空航天大学 | Method and device for recommending applications |
| CN103544220B (en) * | 2013-09-29 | 2017-04-05 | 北京航空航天大学 | Using recommendation method and apparatus |
| CN104518954A (en) * | 2013-09-30 | 2015-04-15 | 腾讯科技（深圳）有限公司 | Method, device and open platform for transmitting information |
| CN104518954B (en) * | 2013-09-30 | 2018-11-16 | 腾讯科技（深圳）有限公司 | Method for sending information, device and open platform |
| CN103595758A (en) * | 2013-10-11 | 2014-02-19 | 北京奇虎科技有限公司 | Method and device for recommending software |
| CN103595758B (en) * | 2013-10-11 | 2017-03-08 | 北京奇虎科技有限公司 | Recommend the method and device of software |
| CN103744966B (en) * | 2014-01-07 | 2018-06-22 | Tcl集团股份有限公司 | A kind of item recommendation method, device |
| CN103744966A (en) * | 2014-01-07 | 2014-04-23 | Tcl集团股份有限公司 | Item recommendation method and device |
| CN103838884A (en) * | 2014-03-31 | 2014-06-04 | 联想(北京)有限公司 | Information processing equipment and information processing method |
| CN103838884B (en) * | 2014-03-31 | 2017-03-01 | 联想(北京)有限公司 | Messaging device and information processing method |
| CN103902729A (en) * | 2014-04-14 | 2014-07-02 | 广州金山网络科技有限公司 | Method and device for recommending application program |
| CN105095305B (en) * | 2014-05-20 | 2019-03-08 | 深圳市腾讯计算机系统有限公司 | A kind of generation method and device of personal page |
| CN105095305A (en) * | 2014-05-20 | 2015-11-25 | 深圳市腾讯计算机系统有限公司 | Method and device for generating personalized page |
| CN105279079A (en) * | 2014-06-25 | 2016-01-27 | 腾讯科技（深圳）有限公司 | Application performance estimating method, apparatus and system |
| CN104158865A (en) * | 2014-08-01 | 2014-11-19 | 北京奇虎科技有限公司 | Method and system for pushing applications to terminal |
| CN104166696B (en) * | 2014-08-01 | 2018-07-27 | 小米科技有限责任公司 | Application program method for pushing and device |
| CN104182545A (en) * | 2014-09-05 | 2014-12-03 | 北京金山安全软件有限公司 | Application program recommendation method and device |
| CN104270429A (en) * | 2014-09-19 | 2015-01-07 | 北京奇虎科技有限公司 | Method and device for pushing application to terminal |
| CN104615661A (en) * | 2015-01-05 | 2015-05-13 | 华为技术有限公司 | Service recommendation method, device and system oriented to cloud platform applications |
| CN104615661B (en) * | 2015-01-05 | 2019-02-19 | 华为技术有限公司 | Service recommendation method, equipment and the system of facing cloud platform application |
| CN104852962A (en) * | 2015-04-09 | 2015-08-19 | 乐视致新电子科技（天津）有限公司 | Method, terminal device, server and system for processing focused information |
| CN107644079A (en) * | 2015-05-22 | 2018-01-30 | 广东欧珀移动通信有限公司 | Method and device and related media production are recommended in one kind application |
| CN107735766A (en) * | 2015-06-05 | 2018-02-23 | 苹果公司 | The system and method for providing recommendation for the proactive property of the user to computing device |
| CN107735766B (en) * | 2015-06-05 | 2021-08-31 | 苹果公司 | System and method for proactively providing recommendations to a user of a computing device |
| CN104991914A (en) * | 2015-06-23 | 2015-10-21 | 腾讯科技（深圳）有限公司 | Application recommendation method and server |
| US10621186B2 (en) | 2015-06-23 | 2020-04-14 | Tencent Technology (Shenzhen) Company Limited | Application recommendation method, server, and computer readable medium |
| WO2016206482A1 (en) * | 2015-06-24 | 2016-12-29 | 腾讯科技（深圳）有限公司 | Service processing method, server, and computer storage medium |
| US10922323B2 (en) | 2015-06-24 | 2021-02-16 | Tencent Technology (Shenzhen) Company Limited | Service processing method, server and computer storage medium |
| CN106452808A (en) * | 2015-08-04 | 2017-02-22 | 北京奇虎科技有限公司 | Data processing method and data processing device |
| CN106445971A (en) * | 2015-08-11 | 2017-02-22 | 北京奇虎科技有限公司 | Application recommendation method and system |
| CN105117440A (en) * | 2015-08-11 | 2015-12-02 | 北京奇虎科技有限公司 | Method and apparatus for determining to-be-recommended application (APP) |
| CN105630957B (en) * | 2015-12-24 | 2019-05-21 | 北京大学 | A kind of application quality method of discrimination and system based on subscriber management application behavior |
| CN105630957A (en) * | 2015-12-24 | 2016-06-01 | 北京大学 | User management application behavior-based application quality distinguishing method and system |
| CN107045688A (en) * | 2016-02-05 | 2017-08-15 | 上海行邑信息科技有限公司 | A kind of control method and device of accurate identification target terminal |
| CN105653343A (en) * | 2016-02-26 | 2016-06-08 | 北京金山安全软件有限公司 | Software display method and device and electronic equipment |
| CN105787053A (en) * | 2016-02-26 | 2016-07-20 | 维沃移动通信有限公司 | Application pushing method and terminal |
| CN107292463A (en) * | 2016-03-30 | 2017-10-24 | 阿里巴巴集团控股有限公司 | A kind of method and system that the project evaluation is carried out to application program |
| CN106096035B (en) * | 2016-06-23 | 2019-11-26 | 维沃移动通信有限公司 | A kind of recommended method and mobile terminal of application program |
| CN106096035A (en) * | 2016-06-23 | 2016-11-09 | 维沃移动通信有限公司 | A kind of recommendation method of application program and mobile terminal |
| WO2018010591A1 (en) * | 2016-07-12 | 2018-01-18 | 腾讯科技（深圳）有限公司 | Information push method and apparatus, server, and storage medium |
| US11449916B2 (en) | 2016-07-12 | 2022-09-20 | Tencent Technology (Shenzhen) Company Limited | Information push method and apparatus, server, and storage medium |
| CN106776906A (en) * | 2016-11-30 | 2017-05-31 | 努比亚技术有限公司 | One kind application clustering method and device |
| CN108319449A (en) * | 2017-01-16 | 2018-07-24 | 北京金山云网络技术有限公司 | A kind of application architecture determines method and device |
| CN108319449B (en) * | 2017-01-16 | 2021-07-20 | 北京金山云网络技术有限公司 | Application program architecture determining method and device |
| WO2018145577A1 (en) * | 2017-02-08 | 2018-08-16 | 腾讯科技（深圳）有限公司 | Facial-expression recommendation method and device |
| US10949000B2 (en) | 2017-02-08 | 2021-03-16 | Tencent Technology (Shenzhen) Company Limited | Sticker recommendation method and apparatus |
| CN106993038B (en) * | 2017-03-31 | 2020-05-29 | 北京猎豹移动科技有限公司 | Application program popularization method and device and server |
| CN106993038A (en) * | 2017-03-31 | 2017-07-28 | 北京猎豹移动科技有限公司 | Promotion method, device and the server of application program |
| CN107133296A (en) * | 2017-04-26 | 2017-09-05 | 努比亚技术有限公司 | A kind of application program recommends method, device and computer-readable recording medium |
| CN107102876A (en) * | 2017-04-26 | 2017-08-29 | 深圳天珑无线科技有限公司 | Application pushing method and device |
| CN107133296B (en) * | 2017-04-26 | 2020-08-21 | 南京心视窗信息科技有限公司 | Application program recommendation method and device and computer readable storage medium |
| CN107229734A (en) * | 2017-06-12 | 2017-10-03 | 深圳市乃斯网络科技有限公司 | Terminal app based on positioning recommends method and system |
| CN109213799A (en) * | 2017-06-29 | 2019-01-15 | 北京搜狗科技发展有限公司 | A kind of recommended method and device of cell dictionary |
| CN109213799B (en) * | 2017-06-29 | 2021-05-25 | 北京搜狗科技发展有限公司 | Recommendation method and device for cell word bank |
| CN107844536A (en) * | 2017-10-18 | 2018-03-27 | 西安万像电子科技有限公司 | The methods, devices and systems of application program selection |
| CN109872206A (en) * | 2017-12-04 | 2019-06-11 | 北京京东尚科信息技术有限公司 | Assess determination method for parameter, device and computer readable storage medium |
| CN109872206B (en) * | 2017-12-04 | 2022-04-12 | 北京京东尚科信息技术有限公司 | Method and device for determining evaluation parameters and computer-readable storage medium |
| CN108596711B (en) * | 2018-03-28 | 2021-04-23 | 阿里巴巴（中国）有限公司 | Application recommendation method and device and electronic equipment |
| CN108717513A (en) * | 2018-04-27 | 2018-10-30 | 上海爱优威软件开发有限公司 | A kind of information sharing method and system based on terminal operation |
| CN109299349B (en) * | 2018-09-11 | 2021-02-19 | 广州视源电子科技股份有限公司 | Application recommendation method and device, equipment and computer-readable storage medium |
| CN109299349A (en) * | 2018-09-11 | 2019-02-01 | 广州视源电子科技股份有限公司 | Application recommendation method and device, equipment and computer-readable storage medium |
| CN109710857A (en) * | 2018-12-27 | 2019-05-03 | 杭州启迪万华科技产业发展有限公司 | A kind of public platform recommended method and device |
| CN109710850A (en) * | 2018-12-27 | 2019-05-03 | 杭州启迪万华科技产业发展有限公司 | A kind of public platform information association treating method and apparatus |
| CN110175290A (en) * | 2019-05-24 | 2019-08-27 | 竞技世界(成都)网络技术有限公司 | A kind of content delivery method and device |
| CN110175290B (en) * | 2019-05-24 | 2022-03-15 | 竞技世界(成都)网络技术有限公司 | Content pushing method and device |
| CN110688582A (en) * | 2019-11-12 | 2020-01-14 | 广东小天才科技有限公司 | Application recommendation method, application recommendation device and terminal equipment |
| CN112328935A (en) * | 2020-10-29 | 2021-02-05 | 胡培培 | Application program pushing system and method based on big data |
Also Published As
| Publication number | Publication date |
|---|---|
| CN102880501B (en) | 2016-05-25 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102880501B (en) | Implementation method, device and system that application is recommended | |
| CN110442712B (en) | Risk determination method, risk determination device, server and text examination system | |
| CN104753985A (en) | Session list display method and device | |
| CN104750807A (en) | Application recommending method and device | |
| CN107040863A (en) | Real time business recommends method and system | |
| CN103218431A (en) | System and method for identifying and automatically acquiring webpage information | |
| CN113412607B (en) | Content pushing method and device, mobile terminal and storage medium | |
| CN108133390A (en) | For predicting the method and apparatus of user behavior and computing device | |
| CN114595124B (en) | Time sequence abnormity detection model evaluation method, related device and storage medium | |
| CN111259231A (en) | Recommendation method and device for application program | |
| CN105701135A (en) | Application recommendation method and device | |
| CN112949172A (en) | Data processing method and device, machine readable medium and equipment | |
| CN111523035A (en) | Recommendation method, device, server and medium for APP browsing content | |
| CN104376021A (en) | File recommending system and method | |
| CN113269370B (en) | Active user prediction method and device, electronic equipment and readable storage medium | |
| CN107294905A (en) | A kind of method and device for recognizing user | |
| CN112269937B (en) | Method, system and device for calculating user similarity | |
| CN114022196A (en) | Advertisement putting method, device, electronic device and storage medium | |
| US20220167034A1 (en) | Device topological signatures for identifying and classifying mobile device users based on mobile browsing patterns | |
| CN116049808A (en) | Equipment fingerprint acquisition system and method based on big data | |
| CN114328985A (en) | Data processing method and related device | |
| CN107562758B (en) | Information pushing method and device and electronic equipment | |
| CN103024091B (en) | Obtain method and the device of networking client actual physical address | |
| CN105590232A (en) | Client relation generation method and apparatus, and electronic device | |
| CN112905892A (en) | Big data processing method and big data server applied to user portrait mining |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| TR01 | Transfer of patent right | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20220718 Address after: Room 801, 8th floor, No. 104, floors 1-19, building 2, yard 6, Jiuxianqiao Road, Chaoyang District, Beijing 100015 Patentee after: BEIJING QIHOO TECHNOLOGY Co.,Ltd. Address before: 100088 room 112, block D, 28 new street, new street, Xicheng District, Beijing (Desheng Park) Patentee before: BEIJING QIHOO TECHNOLOGY Co.,Ltd. Patentee before: Qizhi software (Beijing) Co.,Ltd. |