WO2014090057A1 - 一种移动应用的推送方法及系统 - Google Patents
一种移动应用的推送方法及系统 Download PDFInfo
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- WO2014090057A1 WO2014090057A1 PCT/CN2013/086685 CN2013086685W WO2014090057A1 WO 2014090057 A1 WO2014090057 A1 WO 2014090057A1 CN 2013086685 W CN2013086685 W CN 2013086685W WO 2014090057 A1 WO2014090057 A1 WO 2014090057A1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
- G06Q30/0631—Item recommendations
Definitions
- the present invention relates to the field of Internet applications, and in particular, to a push method and system for a mobile application.
- the mobile application store pushes some mobile applications to the user when the user downloads or browses the application, and recommends the mobile application to the user.
- the pushing method is to calculate the correlation between the mobile applications according to the user history log, and then according to the correlation and
- the recommendation results are generated by using a recommendation algorithm such as neighboring, collaborative filtering, etc., so the prior art recommends the mobile application by using the correlation between the mobile applications as a recommendation basis.
- the new mobile app does not have a user history log, it is impossible to count the correlation between the newly added mobile app and other mobile apps, so it is not possible to recommend the newly added mobile app to the user when viewing or downloading the mobile app. Users, can't solve the cold boot problem of the new mobile app.
- the invention provides a push method and system for a mobile application, which can effectively improve recommendation The diversity of mobile applications.
- the present invention provides a push method for a mobile application, the method comprising:
- the mobile application that selects the preset recommendation result is pushed to the user as the recommendation result.
- the method for determining the correlation between mobile application categories is:
- the degree of relevance between the mobile application categories is calculated based on the information of each user operating the mobile application in the mobile application store and the correlation between the pre-generated mobile applications.
- the method of pre-generating the correlation between mobile applications is:
- u denotes the mobile application
- m the user set of the mobile application
- ⁇ respectively denotes the user u in the user set U and the "allocated score
- the integer factor, "" represents the total number of mobile applications operated by the user u in the user set U, and represents the average of the total number of mobile applications operated by the user u.
- the weight of the user u in the user set U is >v
- ⁇ ⁇ is: s ap d St x B t apPm ',
- the method for calculating the correlation between mobile application categories is:
- Concept apPn concept ; where concepti and concept j are the mobile application categories to which the mobile application app m and the mobile application app n belong, respectively, R( a pp m , "pp disorder) for the mobile application "pp m and the mobile application ⁇ th.
- the correlation f between them represents the total number of users operating the mobile application ⁇ /
- f app represents the total number of users operating the mobile application
- f app app represents the set of users operating the mobile application ⁇ / and operates the mobile application
- the intersection of the collection of users of app n contains the total number of users.
- the method of pre-generating the weight value of the mobile application is to calculate the weight value w of the mobile application in the mobile application category using the following formula:
- the operation of the mobile application comprises at least one of viewing, downloading and using.
- the method further includes:
- the weight value of the newly added mobile application is obtained by multiplying the average weight value of the top mobile application under the mobile application category to which the new mobile application belongs, by the preset attenuation factor.
- the method for calculating the recommended degree of each mobile application under the mobile application category is:
- r ec a PPm a PPn Riconcept ,, concept) xw ncept] apPn + kx comatt (app m, app n) calculated at the specified mobile applications recommended mobile applications to a user when app m, n the degree of recommendation rec appmappn.;
- the mobile application mobile application category belongs concepti app m, mobile applications, mobile applications n Concept category belongs, the mobile application concept j belonging to the category of the mobile application determines another class 1 J, R ⁇ concept i, concept j ) for the mobile application class 1 J concept and the mobile application class 1 J concept correlation, w ⁇ perhaps e bombard for the mobile application category concept under the mobile application weight value, rama (app m , a / 3 ⁇ 4 ) For mobile applications ⁇ w condiment and the number of properties of the mobile app, the default impact factor.
- the mobile application that selects the preset recommended result number is pushed to the user as a recommendation result, including:
- the recommendation result is pushed to the user, and the ⁇ is the number of preset recommendation results.
- the present invention also provides a push system for a mobile application, the system comprising: a statistical unit, a first computing unit, and a pushing unit;
- a statistical unit configured to determine one or more mobile application categories that have the highest correlation with a mobile application category to which the user-specified mobile application belongs;
- a first calculating unit configured to calculate, according to a weight value of the pre-generated mobile application, a recommendation degree of each mobile application in the mobile application category determined by the statistical unit;
- the pushing unit is configured to: according to the principle that the recommendation degree of each mobile application under the mobile application category determined by the statistical unit is high to low, the mobile application that selects the preset recommended result number is pushed to the user as a recommendation result.
- the system further includes: a second calculating unit, configured to: Pre-generate the relevance of mobile app categories, specifically for:
- the mobile application operated by each user is classified according to the category information of each mobile application in the ontology library of the mobile application; and the calculation is performed according to the information of each user operating the mobile application in the mobile application store and the correlation between the pre-generated mobile applications.
- the relevance between mobile app categories is defined by the mobile application operated by each user.
- the system further includes: a third calculating unit, configured to pre-generate a correlation between the mobile applications, specifically for:
- U represents a user set that simultaneously operates the mobile application ⁇ /3 ⁇ 4 and the mobile application ⁇ / ⁇ recreational, and 3 ⁇ 4 denotes a score assigned to the user u in the user set U as ⁇ / ⁇ and ⁇ /7, respectively; w " The weight of the user u in the user set U, K, ⁇ and the preset tune
- the integer factor which represents the total number of mobile applications operated by the user u in the user set U, and represents the average of the total number of mobile applications operated by the user u.
- the user u assigns a score to the mobile application ⁇ TM
- the first operation mobile application, Craig ⁇ type, ⁇ indicates the total number of types of operations mobile application m, indicates the basic score of the user u operating the mobile application, m ;
- B is an indication of whether the user U performs the first operation on the mobile application Value or move for user U Apply ⁇ / duration information for the first operation.
- the second calculating unit when calculating the correlation between the mobile application categories, is specifically used to:
- Concept appn concept j
- concept i and concept j are the mobile application categories to which the mobile application app m and the mobile app app n belong, respectively, and R(app m , app n ) is between the mobile app ap Pm and the mobile app app n
- the correlation f represents the total number of users operating the mobile application ⁇ /
- f represents the total number of users operating the mobile application app exert ⁇
- f app app represents the set of users operating the mobile application ⁇ /
- the user operating the mobile application app n The intersection of the collection contains the total number of users.
- the system further includes: a fourth calculating unit, configured to pre-generate a weight value of the mobile application, specifically for:
- the operation of the mobile application comprises at least one of viewing, downloading and using.
- the system further includes: an update unit, configured to add a new mobile application in the mobile application store to the ontology library of the mobile application, and mark the corresponding class for the new mobile application.
- an update unit configured to add a new mobile application in the mobile application store to the ontology library of the mobile application, and mark the corresponding class for the new mobile application.
- Information and attribute information configured to add a new mobile application in the mobile application store to the ontology library of the mobile application, and mark the corresponding class for the new mobile application.
- the fourth calculating unit is further configured to multiply the average weight value of the top mobile application under the mobile application category to which the newly added mobile application belongs, by a preset attenuation factor, to obtain a weight value of the newly added mobile application.
- the first computing unit when the first computing unit calculates the recommendation degree of the mobile application under the mobile application category, the first calculating unit is specifically configured to:
- r ec a PPm a PPn Riconcept ,, concept) xw ncept] apPn + kx comatt (app m, app n) calculated at the specified mobile applications recommended mobile applications to users when ap Pm, n is the degree of recommendation rec appmappn.;
- the mobile application mobile application category belongs concepti app m, mobile applications, mobile applications n Concept category belongs, the mobile application concept j belonging to the category of the mobile application determines another class 1 J, R ⁇ concept i, concept j ) for the mobile application class 1 J concept and the mobile application class 1 J concept correlation, w ⁇ perhaps eiller for the mobile application category concept under the mobile application weight value, rama (app m , a / 3 ⁇ 4 ) For mobile applications ⁇ wheli and the number of properties of the mobile app, the default impact factor.
- the pushing unit is specifically configured to separately extract, from the determined mobile application category, a mobile application with a top recommendation degree; and extract the extracted mobile application according to a recommendation level from high to low.
- the order is sorted, and the top n mobile applications are pushed to the user as the recommended result of the mobile application, and the ⁇ is the preset recommended number of results.
- FIG. 2 is a block diagram showing a preferred embodiment of a push system for implementing a mobile application according to the present invention. detailed description
- the basic idea of the present invention is: determining one or more mobile application categories with the highest relevance to the mobile application category of the mobile application specified by the user according to the relevance of the pre-generated mobile application category; calculating according to the weight value of the pre-generated mobile application a recommendation level of the mobile application under the mobile application category; extracting a mobile application with a top recommendation level under each mobile application category, and one or more mobile applications with the highest recommended degree among the extracted mobile applications according to the preset number of recommended results Pushed to the user as a result of the recommendation.
- FIG. 1 is a schematic flowchart of a preferred embodiment of a method for implementing a mobile application according to the present invention. As shown in FIG. 1, the preferred embodiment includes the following steps:
- Step 101 View or download information of the mobile application according to the user in the mobile application store And the duration information that the user uses the mobile app to calculate the correlation between the mobile apps in the mobile app collection that the user views, downloads, and uses.
- the data platform of the mobile application store stores a user history log when the user uses the mobile application store, and the data platform stores the user history log in a text format and sets a setting in units of a set duration (such as an hourly unit).
- the text of the user history log in the duration is saved to the same file.
- the user history log includes information about the user viewing or downloading the mobile application in the mobile application store and duration information of the user using the mobile application, and may also involve other users.
- the operation information of the mobile application is only taken as an example of the operation of viewing, downloading and using; wherein the information of the user viewing or downloading the mobile application in the mobile application store includes a user identifier (UID), and the user is viewed in the mobile application store.
- UID user identifier
- the identifier of the downloaded mobile application (packagedD) and the time of the mobile application viewed or downloaded by the user in the mobile application store; the duration information of the user using the mobile application includes a user identification (UID).
- R(app m , ap Pn ) ⁇ wêt x app - x app - ( 1 )
- R(app m , app n ) represents the correlation between the mobile application app m and the mobile application app n in the mobile set.
- U represents the simultaneous operation of the mobile application and the mobile application, "the user set, and ⁇ ⁇ respectively represent the scores assigned by the user 11 in the user set U for ⁇ /3 ⁇ 4 and ⁇ ordinate;
- w chorus represents the user u of the user set U
- the weight can be calculated using equation (2): , Nn u +0.5 (
- N represents the total number of mobile applications in the mobile application set, and represents the total number of mobile applications, downloaded mobile applications, and mobile applications used by the user u in the user set U.
- the correlation degree described in the formula (1) is actually calculated by calculating the correlation between the two mobile applications in the mobile application set, and then summing the formula (1) in the calculation movement.
- the BM25 algorithm is used when applying the correlation between the two, but the present invention is not limited to this correlation calculation method, and correlation calculation methods such as transition probability and cosine formula can also be used, and no longer - examples .
- the degree of influence of p is a preset value.
- m pp indicates whether user u views the mobile application, if yes, read is equal to 1, if no, read aDD is equal to 0; download indicates whether user U downloads mobile application app m , ⁇ The result is that download is equal to 1, ⁇ is no, download is equal to 0; M me ⁇ indicates the duration of the user using the mobile application ⁇ , here, the duration of the user using the mobile application ⁇ can be in units such as minutes;
- b is equal to 0.75, which represents the total number of mobile applications viewed by user u, the total number of downloaded mobile applications, and the average of the total number of mobile applications used.
- the correlation between the mobile applications may be periodically calculated. For example, the user history log in the previous month may be extracted every morning, and the correlation between the mobile applications is calculated according to the user history log.
- Step 102 Obtain, according to the mobile application's ontology library, the category information of the mobile application in the mobile application set, and classify the mobile application according to the category information of the mobile application; according to the user viewing or downloading the mobile application information in the mobile application store, the user uses the mobile application.
- the duration letter, and the calculated correlation between the mobile applications calculates the correlation between the mobile application categories.
- the on-body library of the mobile application is in the unit of the identifier (packagedD) of the mobile application, and includes the name, category information, and attribute information corresponding to the identifier of the mobile application.
- the ontology library of the mobile application may be as shown in Table 1. :
- the category information of each mobile application is obtained in the ontology library of the mobile application according to the identifier of the mobile application in the mobile application set, and then according to the category information of the mobile application.
- the mobile application performs classification to obtain one or more mobile application categories corresponding to the mobile application set, according to the calculated mobile application.
- the correlation between the mobile application categories is calculated using equation (4): —— ⁇ x R(app m , app n ) ( 4 ) ⁇ , ⁇ , f 2pPm + f 2pPn where concept i and concept j respectively represent the mobile application category to which the mobile application app m and the mobile application app n belong.
- R(app m , app represents the correlation between the mobile application app m and the mobile application app n in the mobile application set calculated by the public (1), Riconcep ⁇ , concept j ) represents the mobile application category concepti and the mobile application category concept.
- the correlation between the two; / a indicates the total number of users viewing the mobile app, the user who downloaded the mobile app aw ⁇ , and the user using the mobile app, indicating the user viewing the mobile app " ⁇ ", the user who downloaded the mobile app " ⁇ ", and using The total number of users who move the application " ⁇ "; here, the total number of users of the mobile application, the users who download the mobile application, and the users who use the mobile application can be viewed according to the user history log statistics; the user who views the mobile application ⁇ / ⁇ TM, downloads collection of intersection of the sets of mobile application users and the use of mobile applications and view the user's mobile application, users download the mobile application or mobile app app "users It contains the total number of users.
- Step 103 Add a new mobile application in the mobile application store to the mobile application's own library, and mark corresponding category information and attribute information for the newly added mobile application.
- the newly added mobile application in the mobile application store may be added to the ontology library, the package1D is allocated for the newly added mobile application, and the corresponding category information and attribute information are marked.
- the mobile application automatic annotation system can be used according to the name and the introduction of the mobile application provided by the mobile application owner.
- the new mobile app automatically labels the class with additional 'J information and attribute information.
- this step is to solve the problem that the new mobile application cannot be cold-started, and is not a necessary step of the present invention.
- Step 104 Calculate, according to the information that the user views or downloads the mobile application in the mobile application store, and the duration information of the mobile application, the weight value of the non-new mobile application in the mobile application category in the on-body library; The average weight value of the top mobile application under the mobile application category is multiplied by the preset attenuation factor to obtain the weight value of the newly added mobile application.
- the weight value of the mobile application under the mobile application category in the ontology library of the mobile application is calculated by using formula (5):
- ⁇ P the total number of times all mobile apps are viewed in the user history log; indicates the total number of times all mobile apps in the mobile app category are downloaded in the user history, indicating that all mobile apps in the mobile app category are The total duration used in the user history log; & indicates the mobile application, m is viewed in the user history, the corresponding impact factor, and g 2 indicates the impact factor of the mobile application being downloaded in the user history log, indicating the mobile application.
- the newly added mobile application adopts a default weight value, and the default weight value is calculated by using the mobile application category with the highest weight value ( For example, three) the average of the weight values of the mobile application is multiplied by an attenuation factor, which in the preferred embodiment is equal to 0.4.
- Step 105 When receiving the mobile application specified by the user, determining, according to the relevance of the mobile application category, one or more mobile application categories having the highest relevance to the mobile application category of the specified mobile application; calculating the mobile according to the weight value of the mobile application.
- the recommendation level of the mobile application under the application category; the mobile application with the highest recommendation level under each mobile application category is extracted, and one or more mobile applications with the highest recommendation degree in the extracted mobile application are used as the recommendation result according to the preset number of recommended results. Push to the user.
- n is the top mobile application category that is ranked higher than n (such as 2n).
- r ec a PPm a PPn Riconcept ,, concept) xw conceptjapPn + kx comatt (app m, app n) (6) wherein, recommended mobile applications to users in a given mobile applications, the degree of recommendation n, the mobile application app m belongs
- the mobile app category is, mobile app, n belongs to the mobile app category as concept ), mobile app category concept ) is located in the mobile app category
- the mobile application that calculates the recommendation degree is filtered according to the user history log, and the mobile application downloaded or used by the user is deleted, and the mobile application category is used as a unit, and the recommendation degree is large.
- the mobile application under each mobile application category is sorted in a small order, and then the mobile application of the top two rankings of each mobile application category is extracted, and the mobile application extracted from each mobile application category is based on the recommendation degree. Sorting from high to low, according to the preset number of recommended results n, the top n mobile applications are used as recommended results of the mobile application, and the recommendation results are pushed to the user.
- FIG. 2 is a schematic structural diagram of a preferred embodiment of a push system for implementing a mobile application according to the present invention.
- the system includes: a statistical unit 20, a first calculating unit 21, a pushing unit 22, wherein the calculating unit 20 is configured to determine, according to the pre-generated relevance of the mobile application category, one or more mobile application categories having the highest relevance to the mobile application category of the mobile application specified by the user;
- the first calculating unit 21 is configured to calculate, according to a weight value of the pre-generated mobile application, a recommendation degree of the mobile application under the mobile application category;
- the pushing unit 22 is configured to extract a mobile application with a top recommendation level under each mobile application category, and push one or more mobile applications with the highest recommendation degree in the extracted mobile application as a recommendation result to the user according to the preset number of recommended results. .
- the system further includes: a second calculating unit 23 for pre-generating the relevance of the mobile application category;
- the second calculating unit 23 pre-generating the relevance of the mobile application category specifically includes: obtaining the category information of the mobile application according to the ontology library of the mobile application, and classifying the mobile application viewed, downloaded, and used by the user according to the category information of the mobile application;
- the user calculates or correlates the information of the mobile application, the duration information of the user using the mobile application, and the correlation between the pre-generated mobile applications in the mobile application store to calculate the correlation between the mobile application categories.
- the system also includes a third computing unit for pre-generating correlations between mobile applications
- R(app m , app n ) represents the correlation between the mobile application app m and the mobile application ap Pn in the mobile UI set
- U represents the user set of the mobile application app m and the mobile application app n simultaneously
- ⁇ ⁇ respectively Indicates the score assigned by user 11 in the user set U to ⁇ / and ⁇ ordinate
- b is equal to 0.75, which represents the total number of mobile applications viewed, downloaded, and used by user u in user set U, / ⁇ represents the total number of mobile applications viewed by user u, the total number of downloaded mobile applications, and the total number of mobile applications used. average value.
- N represents the total number of mobile applications in the mobile application set, and represents the total number of mobile applications viewed, downloaded, and used by the user u in the user set U.
- the user for mobile applications ⁇ / ⁇ ⁇ ⁇ score is assigned
- s apPm s, x read appm + s 2 download ⁇ + s 3 x usetime apPm ;
- the calculating, by the second calculating unit 23, the correlation between the mobile application categories specifically includes:
- Riconcepti , concept ) ⁇ —— ⁇ x R(app m , app n )
- Concept appn concept j
- concept and concept are the mobile application categories to which the mobile app app m and the mobile app app n belong, respectively, and R( iWP , fl ; ⁇ rang) is the correlation between the mobile app and the mobile app in the mobile app collection.
- Wm represents the total number of users viewing the mobile application ⁇ ,ograph, the user who downloaded the mobile app app m and the user using the mobile app app m
- f apPn indicates the user viewing the mobile app app, the user who downloaded the mobile app n n and The total number of users using the mobile application ap Pn , indicating the user who views the mobile application, the user who downloaded the mobile application, and the user who uses the mobile application ⁇ and the user who views the mobile application ⁇ suggest, download the mobile application ⁇ cca The total number of users included in the intersection of the user or the collection of users using the mobile application " ⁇ ".
- the system further includes a fourth calculating unit 25 for generating a weight value of the mobile application in advance; the fourth calculating unit 25 pre-generating the weight value of the mobile application specifically includes: calculating the mobile application by using the following formula, m in the mobile application category Weight value: Rdu
- ppm , d appm , " ⁇ are mobile applications respectively, the total number of times m is viewed in the user history, the total number of times downloaded, the total length of time used; r concepti , d - , u - , respectively For the mobile application category C. ⁇ The total number of times all mobile apps are viewed in the user history log, the total number of times downloaded, the total duration used; & equals 0.2, equals 0.4, equals 0.4.
- the system further includes: an update unit 26, configured to add a new mobile application in the mobile application store to the on-body library of the mobile application, and mark corresponding category information and attribute information for the newly added mobile application.
- the fourth calculating unit 25 is further configured to multiply the average weight value of the top mobile application under the mobile application category to which the newly added mobile application belongs, by a preset attenuation factor, to obtain a new mobile application of the J. Weight value.
- the calculating, by the first calculating unit 21, the recommendation degree of the mobile application under the mobile application category specifically includes:
- Mobile computing applications category degree of recommendation for each mobile application using the formula:. Rec a PPm a PPn ⁇ ⁇ oncept,, concept) xw conceptjCipPn + kx comatt (app m, app n) where, rec a / 3 ⁇ 4vw "is in a given mobile applications ⁇ recommendation mobile applications to users, the degree of recommendation n, the mobile application category mobile application app m belongs, mobile applications, mobile applications category n belongs concept j, mobile application category concept j located in mobile applications category concept. highest correlation mobile application category, Riconcept ⁇ , concept.) the other type of mobile application 1 J c. "cepi, and mobile application category C.” « ⁇ correlation between, for mobile applications category concept. Move the application down;; the weight value of ⁇ resort, comatt(app m , app n ) for mobile applications ⁇ w salt and mobile The number of the same attribute of m is applied, which is equal to 2.
- the newly added mobile application is added to the ontology library, and the category information and the attribute information are configured. Therefore, when calculating the recommendation degree of the mobile application, it can be based on the ontology library.
- the newly added mobile application is included in the calculation range, effectively calculating the recommendation degree of the newly added mobile application, and can also effectively push the newly added mobile application to the user according to the recommendation degree, thereby effectively solving the cold start of the newly added mobile application. problem.
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EP13863276.5A EP2933770A4 (en) | 2012-12-14 | 2013-11-07 | METHOD AND SYSTEM FOR EDITIONING A MOBILE APPLICATION |
JP2015546823A JP6262764B2 (ja) | 2012-12-14 | 2013-11-07 | モバイルアプリケーションをプッシュする方法及びシステム |
US14/411,846 US9978093B2 (en) | 2012-12-14 | 2013-11-07 | Method and system for pushing mobile application |
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EP2933770A4 (en) | 2016-05-04 |
US20150332373A1 (en) | 2015-11-19 |
EP2933770A1 (en) | 2015-10-21 |
JP6262764B2 (ja) | 2018-01-17 |
CN103020845B (zh) | 2018-08-10 |
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