CN107193829A - Application program recommends method and apparatus - Google Patents
Application program recommends method and apparatus Download PDFInfo
- Publication number
- CN107193829A CN107193829A CN201610144929.0A CN201610144929A CN107193829A CN 107193829 A CN107193829 A CN 107193829A CN 201610144929 A CN201610144929 A CN 201610144929A CN 107193829 A CN107193829 A CN 107193829A
- Authority
- CN
- China
- Prior art keywords
- application program
- application
- recommended range
- fame
- recommended
- 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
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/903—Querying
- G06F16/9032—Query formulation
- G06F16/90324—Query formulation using system suggestions
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Databases & Information Systems (AREA)
- Theoretical Computer Science (AREA)
- Mathematical Physics (AREA)
- Computational Linguistics (AREA)
- Data Mining & Analysis (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Information Transfer Between Computers (AREA)
- Stored Programmes (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
Recommend method and apparatus the invention discloses a kind of application program, methods described includes：Initial fame of each application program in recommended range is set, and based on the fame using each application program of feedback information real-time update in the recommended range；The application recommendation request that user terminal is sent is received, and determines application recommended range corresponding with application recommendation request；According to the fame of the application program in application recommended range, recommendation list is applied in generation, and will be sent using recommendation list to the user terminal.Technical scheme provided in an embodiment of the present invention causes some newborn application programs according to its fame, recommended in corresponding recommended range, newborn application program in the prior art is solved to have no chance at all by the technical problem for recommending displaying interface to user, existing application program recommended technology is optimized, the application program recommended requirements of the growing personalization of people, facilitation are met.
Description
Technical field
Recommend method and apparatus the present embodiments relate to the information processing technology, more particularly to a kind of application program.
Background technology
With the development of information technology, using shop as a kind of brand-new value-added service, provide the user
A kind of conveniently e-commerce platform, can easily be purchased by the application store users on mobile terminal
Buy and download application program and other mobile value-added service products, good experience is brought to user.
But, as the number of applications and species in application shop are more and more, only small part
Application program turns into popular application and is presented in the recommendation interface using shop, and most of newborn application program
Have no chance at all by recommending displaying interface to user, these possible newborn application programs are for user
The higher application program of some use value, by existing application program recommended technology, can not only be used
Family, which has been missed, downloads and using the chance of these application programs, application developer is lost quick exhibition
The chance of these existing application programs.
The content of the invention
The embodiment of the present invention provides a kind of application program and recommends method and apparatus, to optimize existing application program
Recommended technology, meets the application program recommended requirements of the growing personalization of people, facilitation.
In a first aspect, the embodiments of the invention provide a kind of application program recommend method, including：
Initial fame of each application program in recommended range is set, and based on real-time more using feedback information
New fame of each application program in the recommended range；
The application recommendation request that user terminal is sent is received, and determines answer corresponding with the application recommendation request
Use recommended range；
According to the fame of the application program in the application recommended range, recommendation list is applied in generation,
And send the application recommendation list to the user terminal.
In second aspect, the embodiment of the present invention additionally provides a kind of application program recommendation apparatus, including：
Fame determining module, for setting initial fame of each application program in recommended range, and base
In the fame using each application program of feedback information real-time update in the recommended range；
Using recommended range determining module, for receiving the application recommendation request of user terminal transmission, and determine
Application recommended range corresponding with the application recommendation request；
Using recommendation list generation module, for according to the application program in the application recommended range
Recommendation list is applied in fame, generation, and the application recommendation list is sent to the user terminal.
The embodiment of the present invention is based on by the initial fame that is arranged on for each application program in recommended range
Using the technological means of fame of each application program of feedback information real-time update in the recommended range,
So that some newborn application programs are recommended in corresponding recommended range, solved according to its fame
Popular application program is occupied in the recommendation interface in application shop in the prior art, and newborn application program is basic
Have no chance by the technical problem for recommending displaying interface to user, optimize existing application program and recommend skill
Art, meets the application program recommended requirements of the growing personalization of people, facilitation.
Brief description of the drawings
Fig. 1 is the flow chart that a kind of application program that the embodiment of the present invention one is provided recommends method；
Fig. 2 is the flow chart that a kind of application program that the embodiment of the present invention two is provided recommends method；
Fig. 3 is the flow chart that a kind of application program that the embodiment of the present invention three is provided recommends method；
Fig. 4 is a kind of structural representation for application program recommendation apparatus that the embodiment of the present invention four is provided.
Embodiment
The present invention is described in further detail with reference to the accompanying drawings and examples.It is understood that this
The specific embodiment of place description is used only for explaining the present invention, rather than limitation of the invention.Also need in addition
It is noted that illustrate only part related to the present invention for the ease of description, in accompanying drawing and not all knot
Structure.
It also should be noted that, for the ease of description, portion related to the present invention is illustrate only in accompanying drawing
Divide rather than full content.It should be mentioned that some show before exemplary embodiment is discussed in greater detail
Example property embodiment is described as processing or the method described as flow chart.Although flow chart by operations (or
Step) it is described as the processing of order, but many of which operation can be by concurrently, concomitantly or together
When implement.In addition, the order of operations can be rearranged.The processing can when its operations are completed
To be terminated, it is also possible to the additional step being not included in accompanying drawing.The processing can correspond to
Method, function, code, subroutine, subprogram etc..
Embodiment one
Fig. 1 is the flow chart that a kind of application program that the embodiment of the present invention one is provided recommends method, the present embodiment
Method can be performed by application program recommendation apparatus, the device can be by the way of hardware and/or software
To realize, and it can typically be integrated in the server for providing application program recommendation service, with application program
Class client (for example, " XX applies shop " or " XX application markets " etc.) is recommended to use cooperatively.
As shown in figure 1, application program provided in an embodiment of the present invention recommends method to include：
The initial fame of S101, each application program of setting in recommended range, and be based on using feedback information
Fame of each application program of real-time update in the recommended range.
It can also be a functional value using the time as variable that the initial fame, which is specifically as follows a numerical value,.
Certainly, the initial fame of each application program can be with identical, can also be different, can be according to application program
Attribute, initial fame is assigned such as type (amusement, office, social activity), installation kit size etc.
Different values.
Wherein, the use feedback information includes at least one of following：Application program download, application program
In-service evaluation grade point and application program initiation culture.
Specifically, can be according to application program download, the in-service evaluation grade point of application program and application
One or more of combination in the initiation culture of program, each application program of real-time update is recommended described
In the range of fame, the present embodiment is to this and is not limited.
In the present embodiment, the recommended range can be region recommended range, for example：Province, city or ground
Area etc.；Can also be age recommended range, for example：15-20 Sui, 21-30 Sui or 30 years old with first-class；Also
Can be professional recommended range, for example, educational business, financial circles or service trade etc..
By setting initial fame in recommended range for each application program, and according to real using feedback information
The fame of Shi Gengxin different applications, it is possible to achieve in the high popular application program of user satisfaction by just
It is that newborn application program creates the recommendation chance in application program recommends class client while often recommendation.
Specifically, when a newborn application program is issued in " XX application markets ", can be first
For the application program, one initial fame is set, wherein, the initial fame can be one and larger consolidate
Definite value, or it is described just according to the generation of the fame for the application program for currently recommending setting quantity in the top
Beginning fame (for example, average value of the fame of top 10 application program)., can be with by above-mentioned setting
Ensure that newborn application program there can be one preferably to recommend ranking at the beginning of issue, simultaneously as fame
Being can be with the use feedback information real-time update of user, therefore, the good newborn application program of user feedback
Fame can keep or lifted, user feedback difference newborn application program fame then can accordingly under
Drop.
S102, the application recommendation request for receiving user terminal transmission, and determine and the application recommendation request pair
The application recommended range answered.
Wherein, include in the application recommendation request for determining that application corresponding with user terminal is recommended
The user profile of scope, typically, the user profile can include：The geographical location information of user, use
The age information at family and the occupational information of user etc..And then can according to the user profile determine with it is described
The corresponding application recommended range of user profile.
It is preferred that, the recommended range type phase one of the type of the application recommended range and application program in S101
Cause.For example, the recommended range in S101 is the region recommended range divided according to province, then in S102
According to the geographical location information of the user included using recommendation request, it is determined that corresponding with the geographical location information
Province information as applying recommended range.
S103, the fame according to the application program in the application recommended range, generation application are recommended
List, and the application recommendation list is sent to the user terminal.
The operation can specifically include：According to the size of fame, to the application in the application recommended range
Program is ranked up；According to ranking results, obtain setting and recommend the application program of number to generate the application journey
Sequence recommendation list.
The setting recommends number to be preset according to specifically situation is recommended.
Further, the operation can also include：If the number of the application program in the application recommended range
Mesh is less than the setting and recommends number, then obtains the application in recommended range adjacent with the application recommended range
Application program recommendation list described in Program Generating.The benefit so set is：Answering in application recommended range
With program it is fewer when, by by the application program at least one adjacent recommended range be also added to recommendation row
To be recommended in table, the application program recommended in interface of user terminal can be enriched, is also application program
Show there is provided more chances.
The technical scheme that the present embodiment is provided, passes through the initial sound being arranged on for each application program in recommended range
Prestige value, and based on the popularity using each application program of feedback information real-time update in the recommended range
The technological means of value so that some newborn application programs are obtained according to its fame in corresponding recommended range
To recommend, some the frequency applications programs in the prior art that solve are occupied in the recommendation interface in application shop,
And newborn application program is had no chance by the technical problem for recommending displaying interface to user at all, optimize existing
Some application program recommended technologies, meet the growing personalization of people, the application program of facilitation and push away
Recommend demand.
Embodiment two
Fig. 2 is the flow chart that a kind of application program that the embodiment of the present invention two is provided recommends method, the present embodiment
On the basis of the various embodiments described above, it will preferably be based on using each application journey of feedback information real-time update
Fame of the sequence in the recommended range is specifically optimized for：According to formula：N=k (t) * A+B, real-time update
Fame N of each application program in the recommended range；Wherein, k (t) is the application issued time
Monotonic decreasing function；A is the initial fame of application program；B is by application program download, application
The real-time fame that the in-service evaluation grade point of program and the initiation culture of application program are determined jointly.
Accordingly, as shown in Fig. 2 the application program that the present embodiment is provided recommends method to specifically include：
The initial fame of S201, each application program of setting in recommended range, and according to formula：
N=k (t) * A+B, fame N of each application program of real-time update in the recommended range.
Wherein, k (t) is the monotonic decreasing function of application issued time；A is the initial popularity of application program
Value；B is by application program download, the in-service evaluation grade point of application program and the startup of application program
The real-time fame that frequency is determined jointly.
In the present embodiment, in order to realize that the fame of each application program can reflect user to application program
Satisfaction, then will be reduced, therefore over time for the initial fame that newborn application program is provided
When calculating fame N, initial fame A is multiplied with a monotonic decreasing function k (t).
Non-limiting as example, k (t) can be for 1/ (t-T+1) wherein, and t is the system time of real-time update,
T is the issuing time of application program.
In addition, fame B reflects satisfaction of the user to application program in real time, i.e.,：One application program
Download D is bigger, application program in-service evaluation grade point C is higher and application program initiation culture F
More frequent, user is also higher to the satisfaction of the application program.
Typically, can be directly according to formula：B=D+C+F calculates real-time fame B, can also be according to public affairs
Formula B=k1*D+k2*C+k3*F, calculates real-time fame B, wherein, k1, k2 and k3 are setting
Weight coefficient, its value can be preset according to actual conditions, can also be carried out in real time more according to actual conditions
Newly.
Certainly, it will be appreciated by persons skilled in the art that can according to different use demands to k (t) and
B calculation formula is preset, and the present embodiment is to this and is not limited.
Using above-mentioned formula N=k (t) * A+B, each application program of real-time update is in the recommended range
Fame N benefit is：One larger initial fame is set for each application program in advance, this is initial
Fame is gradually reduced with the passage of application issuing time, so that some newborn application programs are one
Start issue or within the issuing time shorter time, according to larger initial fame, apply business
Have an opportunity to be showed in the recommendation interface in shop, if in addition, new life is applied in application program download, application
The in-service evaluation grade point of program and the corresponding real-time fame B of the initiation culture of application program than it is larger when,
It is also possible that application program can continue application shop recommendation interface in showed.
S202, the application recommendation request for receiving user terminal transmission, and determine and the application recommendation request pair
The application recommended range answered.
S203, the fame according to the application program in the application recommended range, generation application are recommended
List, and the application recommendation list is sent to the user terminal.
The present embodiment is by using formula：N=k (t) * A+B, each application program of real-time update is pushed away described
Fame N in the range of recommending so that newborn application program can be recommended according to initial fame, and
Newborn application program real-time popularity than it is larger when, can it is more preferable or it is lasting application shop recommend boundary
Showed in face, realized while the high popular application program of user satisfaction is by normal recommended, will
Newborn application program optimizes existing application program and pushed away by recommending technique effect of the displaying interface to user
Technology is recommended, the application program recommended requirements of the growing personalization of people, facilitation are met.
Embodiment three
Fig. 3 is the flow chart that the application program that the embodiment of the present invention three is provided recommends method, and the present embodiment is upper
On the basis of stating each embodiment, preferably set initial fame of each application program in recommended range it
Before, in addition to：Attribute is sorted out according to setting, the recommended range of each application program is set.
Accordingly, as shown in figure 3, the application program that the present embodiment is provided recommends method to specifically include：
S301, attribute sorted out according to setting, the recommended range of each application program is set.Wherein, the setting
Sorting out attribute includes：Geographical attribute, age attribute or professional attribute.
The recommended range of the application program can be according in geographical attribute, age attribute or professional attribute
A kind of or its any combination is configured, for example, the recommended range of the application program can be
Determined according to geographical attribute, or determined jointly according to geographical attribute and age attribute.
Exemplary, the classification attribute that sets is geographical attribute.Accordingly, according to geographical attribute, set
The recommended range of each application program can specifically include：According to setting regions division rule, by target recommended area
Domain is divided into multiple territory elements；Rule is set according to setting recommended range, respectively each application program is chosen
At least one territory element as each application program recommended range.The benefit so set is：By should
Recommended with program in its at least one corresponding territory element, rather than recommended in whole target in region
Recommend, newborn application program can be avoided to recommend to recommend in region in whole target and be likely to decrease user's body
The problem of testing.
Wherein, the setting regions division rule be region division set in advance rule, be specifically as follows by
Target recommends region to be divided according to different granularities such as country, province, district and city, county, cell.Institute
Stating target recommends region to be the whole world, some continent, some country etc..
The setting recommended range sets rule to set rule for recommended range set in advance, exemplary,
The geographical position that can be registered according to application issued person to be recommended, and/or answering by application program to be recommended
The geographical position determined with content, is that application program to be recommended chooses corresponding geographical recommended range.
If for example, the application content of application program is " Jiangsu dish way is complete works of " or " prevents Arid Area
When solarization study course " etc. has the content of obvious regional characteristic, it can be determined according to the application content of the application program
Geographical position, be that application program to be recommended is chosen correspondingly for example, Jiangsu Province or Arid Area etc.
Manage recommended range.
More generally, one or more territory element can be randomly choosed, as with application program to be recommended
Corresponding recommended range.
The initial fame of S302, each application program of setting in recommended range, and be based on using feedback information
Fame of each application program of real-time update in the recommended range.
Further, based on using each application program of feedback information real-time update in the recommended range
While interior fame, it can also include：According to sound of each application program in the recommended range
Prestige value, adjusts the recommended range of each application program in real time.
The recommended range for adjusting the application program in real time can include adding or reduction recommended range.
Wherein, the fame according to each application program in the recommended range, adjustment is each in real time
The recommended range of the application program can specifically include：If destination application is in target recommended range
Target fame meet the first threshold condition, then be that the destination application adds new recommended range,
And initial fame of the destination application in the recommended range added is set to the target fame；
If target fame of the destination application in target recommended range meets the second threshold condition, for institute
State destination application reduction recommended range.
The destination application can be any application in server, and the target recommended range is
Recommended range corresponding with the destination application, the target fame be and the destination application
Corresponding fame.
In a specific example, an application program " XX guides " is pushing away set by it after distribution
Scope is recommended for " Tianjin ", " Beijing " and " Langfang ", initial fame corresponding with the recommended range
For 1000, over time, if the fame is decreased to 200, illustrate that user applies journey to this
The satisfaction of sequence is not high, therefore, it can reduce the recommended range of the application program, recommends for example, deleting
" Tianjin " in scope, now, recommends if received again using recommended range for the application of " Tianjin "
Request, then will not recommend user by " XX guides "；On the other hand, if fame value added 2800,
Then illustrate that user is higher to the satisfaction of the application program, therefore can expand the recommended range of the application program,
For example, increase recommended range " Qinhuangdao ", and initial fame corresponding with " Qinhuangdao " is set to
2800, now, can if received again using the application recommendation request that recommended range is " Qinhuangdao "
" XX guides " is recommended into user.
The benefit so set is：The principle run a shop by simulating in actual life, according to application program in phase
The fame in recommended range is answered, the recommended range of each application program is adjusted in real time, when a new life should
It is able to program according to initial fame in recommended range after recommendation, if the newborn application program is being recommended
In the range of acceptance it is higher, its fame then expands the recommended range of the newborn application program than larger,
Conversely, after a newborn application program is able to recommendation according to initial fame in recommended range, if should
Acceptance is than relatively low in recommended range for newborn application program, and its fame is smaller, then this is new for scaled-back
The recommended range of raw application program, has reached to adjust the acceptance of application program in real time according to user and has answered
With the technique effect of program recommended range.
S303, the application recommendation request for receiving user terminal transmission, and determine and the application recommendation request pair
The application recommended range answered.
S304, the fame according to the application program in the application recommended range, generation application are recommended
List, and the application recommendation list is sent to the user terminal.
The technical scheme that the present embodiment is provided, by the classification attribute of setting, sets the recommendation of each application program
Scope so that newborn application program has an opportunity to be recommended in corresponding recommended range according to initial fame,
And the fame according to application program in the recommended range, the recommendation of each application program is adjusted in real time
Scope, application program recommended range can be adjusted in real time according to user to the acceptance of application program by having reached
Technique effect, realizes while new life application is recommended into user, farthest reduces to majority
The interference of user, Consumer's Experience effect is also ensure that while existing application program recommended technology is optimized.
Example IV
Fig. 4 is the structural representation for the application program recommendation apparatus that the embodiment of the present invention four is provided, the application
Program recommendation apparatus is arranged in application program recommendation server, as shown in figure 4, described device includes：
Fame determining module 41, for setting initial fame of each application program in recommended range, and
Based on the fame using each application program of feedback information real-time update in the recommended range；
Using recommended range determining module 42, the application recommendation request for receiving user terminal transmission, and really
Fixed application recommended range corresponding with the application recommendation request；
Using recommendation list generation module 43, for the institute according to the application program in the application recommended range
Fame is stated, recommendation list is applied in generation, and the application recommendation list is sent to the user terminal.
The technical scheme that the present embodiment is provided, passes through the initial sound being arranged on for each application program in recommended range
Prestige value, and based on the popularity using each application program of feedback information real-time update in the recommended range
The technological means of value so that some newborn application programs are obtained according to its fame in corresponding recommended range
To recommend, some the frequency applications programs in the prior art that solve are occupied in the recommendation interface in application shop,
And newborn application program is had no chance by the technical problem for recommending displaying interface to user at all, optimize existing
Some application program recommended technologies, meet the growing personalization of people, the application program of facilitation and push away
Recommend demand.
On the basis of the various embodiments described above, the use feedback information can include at least one of following：
The in-service evaluation grade point and the initiation culture of application program of application program download, application program.
On the basis of the various embodiments described above, the fame determining module is based on real-time more using feedback information
Newly fame of each application program in the recommended range is specially：
According to formula：N=k (t) * A+B, sound of each application program of real-time update in the recommended range
Prestige value N；
Wherein, k (t) is the monotonic decreasing function of application issued time；A is the initial popularity of application program
Value；B is by application program download, the in-service evaluation grade point of application program and the startup of application program
The real-time fame that frequency is determined jointly.
On the basis of the various embodiments described above, it can also include：
Recommended range setup module, for set the initial fame of each application program in recommended range it
Before, attribute is sorted out according to setting, the recommended range of each application program is set；Wherein, the classification attribute bag
Include：Geographical attribute, age attribute or professional attribute.
On the basis of the various embodiments described above, the classification attribute that sets is geographical attribute, the recommended range
Setup module specifically can be used for：
According to setting regions division rule, target recommendation region is divided into multiple territory elements；
Rule is set according to setting recommended range, respectively each application program chooses at least one territory element work
For the recommended range of each application program.
On the basis of the various embodiments described above, it can also include：
Recommended range adjusting module, for existing based on use each application program of feedback information real-time update
While fame in the recommended range, according to sound of each application program in the recommended range
Prestige value, adjusts the recommended range of each application program in real time.
On the basis of the various embodiments described above, the recommended range adjusting module specifically can be used for：
If target fame of the destination application in target recommended range meets the first threshold condition,
New recommended range is added for the destination application, and by destination application in the recommendation model added
Initial fame in enclosing is set to the target fame；
If target fame of the destination application in target recommended range meets the second threshold condition,
Reduce recommended range for the destination application.
On the basis of the various embodiments described above, the application recommendation list generation module specifically can be used for：
According to the size of fame, the application program in the application recommended range is ranked up；
According to ranking results, obtain setting and recommend the application program of number to generate the application program recommendation list.
On the basis of the various embodiments described above, the application recommendation list generation module specifically can be also used for：
If the number of the application program in the application recommended range be less than the recommendation number, obtain with
Application program in the adjacent recommended range of the application recommended range generates the application program recommendation list.
The application program recommendation apparatus that the embodiment of the present invention is provided can be used for execution any embodiment of the present invention to carry
The application program of confession recommends method, possesses corresponding functional module, realizes identical beneficial effect.
Note, above are only presently preferred embodiments of the present invention and institute's application technology principle.Those skilled in the art
It will be appreciated that the invention is not restricted to specific embodiment described here, can enter for a person skilled in the art
Row it is various it is obvious change, readjust and substitute without departing from protection scope of the present invention.Therefore, though
So the present invention is described in further detail by above example, but the present invention be not limited only to
Upper embodiment, without departing from the inventive concept, can also include other more equivalent embodiments,
And the scope of the present invention is determined by scope of the appended claims.
Claims (18)
1. a kind of application program recommends method, it is characterised in that including：
Initial fame of each application program in recommended range is set, and based on real-time more using feedback information
New fame of each application program in the recommended range；
The application recommendation request that user terminal is sent is received, and determines answer corresponding with the application recommendation request
Use recommended range；
According to the fame of the application program in the application recommended range, recommendation list is applied in generation,
And send the application recommendation list to the user terminal.
2. according to the method described in claim 1, it is characterised in that the use feedback information includes following
At least one of：
The in-service evaluation grade point and the initiation culture of application program of application program download, application program.
3. method according to claim 2, it is characterised in that based on use feedback information real-time update
Fame of each application program in the recommended range includes：
According to formula：N=k (t) * A+B, sound of each application program of real-time update in the recommended range
Prestige value N；
Wherein, k (t) is the monotonic decreasing function of application issued time；A is the initial popularity of application program
Value；B is by application program download, the in-service evaluation grade point of application program and the startup of application program
The real-time fame that frequency is determined jointly.
4. according to the method described in claim 1, it is characterised in that recommending model setting each application program
Before initial fame in enclosing, in addition to：
Attribute is sorted out according to setting, the recommended range of each application program is set；Wherein, category is sorted out in the setting
Property includes：Geographical attribute, age attribute or professional attribute.
5. method according to claim 4, it is characterised in that according to geographical attribute, sets each application
The recommended range of program is specifically included：
According to setting regions division rule, target recommendation region is divided into multiple territory elements；
Rule is set according to setting recommended range, respectively each application program chooses at least one territory element work
For the recommended range of each application program.
6. the method according to claim 4 or 5, it is characterised in that based on real using feedback information
While fame of each application programs of Shi Gengxin in the recommended range, in addition to：
According to fame of each application program in the recommended range, each application journey is adjusted in real time
The recommended range of sequence.
7. method according to claim 6, it is characterised in that according to each application program described
Fame in recommended range, the recommended range that each application program is adjusted in real time is specifically included：
If target fame of the destination application in target recommended range meets the first threshold condition,
New recommended range is added for the destination application, and by destination application in the recommendation model added
Initial fame in enclosing is set to the target fame；
If target fame of the destination application in target recommended range meets the second threshold condition,
Reduce recommended range for the destination application.
8. according to the method described in claim 1, it is characterised in that according in the application recommended range
Recommendation list is applied in the fame of application program, generation, and the application recommendation list is sent to institute
Stating user terminal includes：
According to the size of fame, the application program in the application recommended range is ranked up；
According to ranking results, obtain setting and recommend the application program of number to generate the application program recommendation list.
9. method according to claim 8, it is characterised in that according in the application recommended range
Recommendation list is applied in the fame of application program, generation, and the application recommendation list is sent to institute
Stating user terminal also includes：
If the number of the application program in the application recommended range, which is less than the setting, recommends number, obtain
The application program in recommended range adjacent with the application recommended range is taken to generate the application program recommendation list.
10. a kind of application program recommendation apparatus, it is characterised in that including：
Fame determining module, for setting initial fame of each application program in recommended range, and base
In the fame using each application program of feedback information real-time update in the recommended range；
Using recommended range determining module, for receiving the application recommendation request of user terminal transmission, and determine
Application recommended range corresponding with the application recommendation request；
Using recommendation list generation module, for according to the application program in the application recommended range
Recommendation list is applied in fame, generation, and the application recommendation list is sent to the user terminal.
11. device according to claim 10, it is characterised in that under the use feedback information includes
State at least one：
The in-service evaluation grade point and the initiation culture of application program of application program download, application program.
12. device according to claim 11, it is characterised in that the fame determining module is based on
It is specially using fame of each application program of feedback information real-time update in the recommended range：
According to formula：N=k (t) * A+B, sound of each application program of real-time update in the recommended range
Prestige value N；
Wherein, k (t) is the monotonic decreasing function of application issued time；A is the initial popularity of application program
Value；B is by application program download, the in-service evaluation grade point of application program and the startup of application program
The real-time fame that frequency is determined jointly.
13. device according to claim 10, it is characterised in that also include：
Recommended range setup module, for set the initial fame of each application program in recommended range it
Before, attribute is sorted out according to setting, the recommended range of each application program is set；Wherein, the classification attribute bag
Include：Geographical attribute, age attribute or professional attribute.
14. device according to claim 13, it is characterised in that the classification attribute that sets is geography
Attribute, the recommended range setup module specifically for：
According to setting regions division rule, target recommendation region is divided into multiple territory elements；
Rule is set according to setting recommended range, respectively each application program chooses at least one territory element work
For the recommended range of each application program.
15. the device according to claim 13 or 14, it is characterised in that also include：
Recommended range adjusting module, for existing based on use each application program of feedback information real-time update
While fame in the recommended range, according to sound of each application program in the recommended range
Prestige value, adjusts the recommended range of each application program in real time.
16. device according to claim 15, it is characterised in that the recommended range adjusting module tool
Body is used for：
If target fame of the destination application in target recommended range meets the first threshold condition,
New recommended range is added for the destination application, and by destination application in the recommendation model added
Initial fame in enclosing is set to the target fame；
If target fame of the destination application in target recommended range meets the second threshold condition,
Reduce recommended range for the destination application.
17. device according to claim 10, it is characterised in that the application recommendation list generates mould
Block specifically for：
According to the size of fame, the application program in the application recommended range is ranked up；
According to ranking results, obtain setting and recommend the application program of number to generate the application program recommendation list.
18. device according to claim 17, it is characterised in that the application recommendation list generates mould
Block is specifically additionally operable to：
If the number of the application program in the application recommended range, which is less than the setting, recommends number, obtain
The application program in recommended range adjacent with the application recommended range is taken to generate the application program recommendation list.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610144929.0A CN107193829B (en) | 2016-03-14 | 2016-03-14 | Application program recommendation method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610144929.0A CN107193829B (en) | 2016-03-14 | 2016-03-14 | Application program recommendation method and device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN107193829A true CN107193829A (en) | 2017-09-22 |
| CN107193829B CN107193829B (en) | 2021-01-26 |
Family
ID=59870696
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610144929.0A Active CN107193829B (en) | 2016-03-14 | 2016-03-14 | Application program recommendation method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107193829B (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109756868A (en) * | 2017-11-01 | 2019-05-14 | 中国移动通信集团终端有限公司 | Recommended method, device, equipment and the medium of application program |
| CN110110221A (en) * | 2019-03-22 | 2019-08-09 | 浙江非线数联科技有限公司 | Government data intelligent recommendation method and system |
| CN111314402A (en) * | 2018-12-12 | 2020-06-19 | 深圳兆日科技股份有限公司 | Web application publishing method and device, computer equipment and storage medium |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2005067295A1 (en) * | 2003-12-29 | 2005-07-21 | Koninklijke Philips Electronics N.V. | Method and apparatus for content recommendation |
| CN102968987A (en) * | 2012-11-19 | 2013-03-13 | 百度在线网络技术（北京）有限公司 | Speech recognition method and system |
| CN103020845A (en) * | 2012-12-14 | 2013-04-03 | 百度在线网络技术（北京）有限公司 | Mobile application pushing method and system |
| CN103617075A (en) * | 2013-12-04 | 2014-03-05 | 百度在线网络技术（北京）有限公司 | Application program recommending method, system and server |
| CN103617543A (en) * | 2013-11-25 | 2014-03-05 | 百度在线网络技术（北京）有限公司 | Recommendation method and device of application programs |
| 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 |
| CN104090967A (en) * | 2014-07-16 | 2014-10-08 | 北京智谷睿拓技术服务有限公司 | Application program recommending method and device |
| CN104991914A (en) * | 2015-06-23 | 2015-10-21 | 腾讯科技（深圳）有限公司 | Application recommendation method and server |
-
2016
- 2016-03-14 CN CN201610144929.0A patent/CN107193829B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2005067295A1 (en) * | 2003-12-29 | 2005-07-21 | Koninklijke Philips Electronics N.V. | Method and apparatus for content recommendation |
| CN102968987A (en) * | 2012-11-19 | 2013-03-13 | 百度在线网络技术（北京）有限公司 | Speech recognition method and system |
| CN103020845A (en) * | 2012-12-14 | 2013-04-03 | 百度在线网络技术（北京）有限公司 | Mobile application pushing method and system |
| CN103617543A (en) * | 2013-11-25 | 2014-03-05 | 百度在线网络技术（北京）有限公司 | Recommendation method and device of application programs |
| CN103617075A (en) * | 2013-12-04 | 2014-03-05 | 百度在线网络技术（北京）有限公司 | Application program recommending method, system and server |
| 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 |
| CN104090967A (en) * | 2014-07-16 | 2014-10-08 | 北京智谷睿拓技术服务有限公司 | Application program recommending method and device |
| CN104991914A (en) * | 2015-06-23 | 2015-10-21 | 腾讯科技（深圳）有限公司 | Application recommendation method and server |
Non-Patent Citations (1)
| Title |
|---|
| 沈红: "智慧旅游背景下智能手机App的旅游应用研究", 《中国优秀硕士学位论文全文数据库》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109756868A (en) * | 2017-11-01 | 2019-05-14 | 中国移动通信集团终端有限公司 | Recommended method, device, equipment and the medium of application program |
| CN111314402A (en) * | 2018-12-12 | 2020-06-19 | 深圳兆日科技股份有限公司 | Web application publishing method and device, computer equipment and storage medium |
| CN110110221A (en) * | 2019-03-22 | 2019-08-09 | 浙江非线数联科技有限公司 | Government data intelligent recommendation method and system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN107193829B (en) | 2021-01-26 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Stidham | Pricing and capacity decisions for a service facility: Stability and multiple local optima | |
| CN105677831A (en) | Method and device for determining recommended commercial tenants | |
| CN108734297A (en) | The machine learning commending system of the performance optimization of electronic content items for network transmission | |
| CN104317806B (en) | Financial data inquiry method and financial data system | |
| CN107193829A (en) | Application program recommends method and apparatus | |
| CN104756143A (en) | Obtaining event reviews | |
| CN109146741A (en) | A kind of course method for pushing, device and equipment based on capability comparison | |
| CN106294831B (en) | Information recommendation method and electronic equipment | |
| JPWO2012039048A1 (en) | Questionnaire creation support system, questionnaire execution apparatus, and recording medium | |
| CN109710665A (en) | Report downloading method, apparatus, equipment and readable storage medium storing program for executing | |
| JP6352951B2 (en) | Display promotional information | |
| Tseng et al. | An integrated model for analyzing the development of the 4G telecommunications market in Taiwan | |
| US11625757B1 (en) | Hybrid selection of target for advertisement campaign | |
| CN110709867A (en) | Reservation accepting device and reservation accepting program | |
| AU2017203619B2 (en) | Searching available rental vehicles based on adjustable parameters | |
| US20150142482A1 (en) | Search engine for identifying business travel proposals | |
| CN109075987A (en) | Optimize digital assembly analysis system | |
| Louviere | Modeling single individuals: the journey from psych lab to the app store | |
| CN110826786A (en) | Method and device for predicting number of target place population and storage medium | |
| CN106250433A (en) | A kind of dynamically APP application methods of exhibiting and terminal unit | |
| CN102405472B (en) | Method and system for rating items | |
| CN108320212B (en) | Flight information interaction method | |
| KR20170128429A (en) | Service processing method, server and computer storage medium | |
| CN111080454A (en) | Asset combination transaction processing method and device | |
| WO2016070591A1 (en) | Method and system for processing teaching resource |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |