WO2019172488A1 - Procédé et dispositif d'analyse de pertinence entre des applications - Google Patents

Procédé et dispositif d'analyse de pertinence entre des applications Download PDF

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Publication number
WO2019172488A1
WO2019172488A1 PCT/KR2018/008119 KR2018008119W WO2019172488A1 WO 2019172488 A1 WO2019172488 A1 WO 2019172488A1 KR 2018008119 W KR2018008119 W KR 2018008119W WO 2019172488 A1 WO2019172488 A1 WO 2019172488A1
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mobile terminals
kth
association
ratios
applications
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PCT/KR2018/008119
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English (en)
Korean (ko)
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김찬웅
허승필
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주식회사 텐디
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Publication of WO2019172488A1 publication Critical patent/WO2019172488A1/fr

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • 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
    • G06F16/95—Retrieval from the web
    • G06F16/958—Organisation or management of web site content, e.g. publishing, maintaining pages or automatic linking

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  • the present invention relates to a technique for analyzing associations between mobile applications, and more particularly, to a method for analyzing associations between applications and an apparatus for analyzing associations between applications.
  • an application development company or an open market that sells applications attempts to analyze the degree of association between applications and use the results of the analysis in application advertisement.
  • the open market provides a service for recommending applications associated with the specific application.
  • the conventional similar application recommendation service recommends an application associated with the specific application based on a subjective preference evaluation result given to the other applications by the user of the specific application.
  • One object of the present invention to solve the above problems is to provide a method and apparatus that can objectively analyze the degree of association between mobile applications.
  • the main server is the identification ID of each of the plurality of mobile terminals and each of the plurality of mobile terminals Receiving installation log data including a list of applications installed in the database and storing the installation log data in a database, wherein the main server stores the first through the plurality of mobile terminals based on the installation log data of the plurality of mobile terminals stored in the database; K (k is a positive integer) determining first to kth overall ratios corresponding to the proportion of mobile terminals in which each of the applications is installed, and wherein the main server has the installation log data of the plurality of mobile terminals stored in the database.
  • Target applications are installed based on Among the mobile terminals, first to kth intersection ratios corresponding to the ratios of the mobile terminals with each of the first to kth applications installed are determined, and the main server determines the first to kth overall ratios and the first to kth ratios. First to kth association indices indicating an association between the target application and each of the first to kth applications are determined based on the to k th intersection ratios.
  • an apparatus for analyzing correlation between applications includes a database, a data receiving unit, a ratio calculation unit, and an association analysis unit.
  • the data receiver receives and stores installation log data including identification IDs of each of the plurality of mobile terminals and a list of applications installed in each of the plurality of mobile terminals, in the database.
  • the ratio calculation unit may be configured to determine a ratio of mobile terminals to which first to kth (k is positive integer) applications are installed among the plurality of mobile terminals based on the installation log data of the plurality of mobile terminals stored in the database.
  • the association analysis unit may further include first to kth representations indicating an association between the target application and each of the first to kth applications based on the first to kth overall ratios and the first to kth cross ratios. Determine k association indices.
  • An association analysis method between applications according to embodiments of the present invention may effectively improve the objectivity and accuracy of the association analysis between applications.
  • FIG. 1 is a diagram illustrating an association analysis system between applications according to an exemplary embodiment of the present invention.
  • FIG. 2 is a diagram illustrating an example of installation log data transmitted from each of a plurality of mobile terminals included in an association analysis system shown in FIG. 1.
  • FIG. 3 is a block diagram illustrating an example of a main server included in an association analysis system between applications illustrated in FIG. 1.
  • FIG. 4 is a diagram illustrating an example of a database included in the main server of FIG. 3.
  • FIG. 5 is a flowchart illustrating a method for analyzing association between applications according to an embodiment of the present invention.
  • FIG. 6 is a flowchart illustrating an example of determining first to kth overall ratios corresponding to a ratio of mobile terminals in which first to kth applications are installed among the plurality of mobile terminals of FIG. 5.
  • FIG. 7 is a flowchart illustrating an example of determining first to k th intersection ratios corresponding to a ratio of mobile terminals in which the first to k th applications are installed among the mobile terminals in which the target application of FIG. 5 is installed.
  • FIG. 8 is a first through k-th association index indicating an association degree between the target application and each of the first to kth applications based on the first to kth overall ratios and the first to kth intersection ratios of FIG. 5. Is a flow chart showing an example of the steps of determining them.
  • FIG. 1 is a diagram illustrating an association analysis system between applications according to an exemplary embodiment of the present invention.
  • the correlation analysis system 10 between applications may include a plurality of mobile terminals 100, a data server 200, and a main server 300.
  • Each of the plurality of mobile terminals 100 may internally store a unique identification ID.
  • the identification ID may be an advertising ID uniquely assigned to each mobile terminal for the purpose of utilizing the advertisement.
  • Each of the plurality of mobile terminals 100 may download and install various types of applications through wireless communication and execute the installed applications.
  • Each of the plurality of mobile terminals 100 stores installation log data I_LOG including the identification ID of each of the plurality of mobile terminals 100 and a list of all applications installed in each of the plurality of mobile terminals 100.
  • the server 200 may transmit the data.
  • At least one of the applications installed in each of the plurality of mobile terminals 100 may include an installation log data transmission module.
  • pre-appointed applications among applications registered in the open market supplying applications may include the installation log data transmission module in advance.
  • the installation log data transmission module may also be installed in the mobile terminal 100.
  • Installation log data transmission module is automatically executed in the mobile terminal 100 to the identification ID of the mobile terminal 100 and the mobile terminal 100.
  • Installation log data (I_LOG) including a list of installed applications may be transmitted to the data server 200.
  • FIG. 2 is a diagram illustrating an example of installation log data transmitted from each of a plurality of mobile terminals included in an association analysis system shown in FIG. 1.
  • the installation log data I_LOG includes semi-structured data including an identification ID ADID of the mobile terminal 100 and a list APP_LIST of applications installed in the mobile terminal 100. Can be.
  • the installation log data I_LOG may further include a transmission date, an Internet Protocol (IP) address of the mobile terminal 100, and a model name of the mobile terminal 100.
  • IP Internet Protocol
  • the data server 200 may receive and store installation log data I_LOG transmitted from each of the plurality of mobile terminals 100.
  • the data server 200 may transmit the installation log data I_LOG received from each of the plurality of mobile terminals 100 to the main server 300 periodically or aperiodically.
  • the main server 300 may receive the installation log data I_LOG of the plurality of mobile terminals 100 from the data server 200 and store it in a database.
  • the main server 300 may receive the target application information T_APP indicating the target application.
  • the target application information T_APP may be a name of the target application.
  • the main server 300 may receive the target application information (T_APP) through the input of the administrator.
  • T_APP target application information
  • the main server 300 may receive target application information T_APP from an external device through a network.
  • the main server 300 may include first, second, and third marks indicating an association degree between the target application and each of the first to k th applications based on the installation log data I_LOG of the plurality of mobile terminals 100 stored in the database.
  • k association indices RI_1 to RI_k may be determined. Where k represents a positive integer.
  • the main server 300 may operate as an association analysis device that analyzes the association between the target application and each of the first to k th applications.
  • FIG. 3 is a block diagram illustrating an example of a main server included in an association analysis system between applications illustrated in FIG. 1.
  • the main server 300 may include a data receiver 310, a database (DB) 320, a ratio calculator 330, and an association analysis unit 340.
  • DB database
  • the main server 300 may include a data receiver 310, a database (DB) 320, a ratio calculator 330, and an association analysis unit 340.
  • the data receiver 310 includes an installation log including an identification ID (ADID) of each of the plurality of mobile terminals 100 and a list (APP_LIST) of applications installed in each of the plurality of mobile terminals 100 from the data server 200.
  • the data I_LOG may be received and stored in the database 320.
  • FIG. 4 is a diagram illustrating an example of a database included in the main server of FIG. 3.
  • the database 320 may include an identification ID field ADID_F and an application list field APP_LIST_F.
  • the identification ID ADID included in the installation log data I_LOG is stored in the database 320.
  • the list of applications APP_LIST stored in the identification ID field ADID_F and included in the installation log data I_LOG may be stored in the application list field APP_LIST_F of the database 320.
  • applications such as APP1, APP3, and APP5 are installed in the mobile terminal 100 in which the identification ID ADID corresponds to ADID1, and the mobile terminal 100 in which the identification ID ADID corresponds to ADID2.
  • applications such as APP2, APP3, and APP6 are installed.
  • the ratio calculator 330 may receive target application information T_APP indicating the target application.
  • the ratio calculator 330 may receive the target application information (T_APP) through the input of the administrator.
  • the ratio calculator 330 may receive target application information T_APP from an external device through a network.
  • the ratio calculator 330 may be configured to store each of the first to k th applications among the plurality of mobile terminals 100 based on the installation log data I_LOG of the plurality of mobile terminals 100 stored in the database 320.
  • the first to kth overall ratios T_RATE_1 to T_RATE_k corresponding to the ratios of the installed mobile terminals 100 may be determined.
  • the ratio calculation unit 330 is based on the installation log data (I_LOG) of the plurality of mobile terminals 100 stored in the database 320 of the first to the first among the mobile terminals 100, the target application is installed; First to k th cross ratios I_RATE_1 to I_RATE_k corresponding to the ratios of the mobile terminals 100 in which k applications are installed may be determined.
  • the first to k-th application to analyze the degree of association with the target application may be predefined in the ratio calculation unit 330.
  • the ratio calculator 330 may be configured to compare the target application with a list APP_LIST of applications included in the installation log data I_LOG of the plurality of mobile terminals 100 stored in the database 320.
  • the first to k th applications may be determined to analyze the degree of association of the first to k th applications.
  • the ratio calculator 330 may provide the first to kth overall ratios T_RATE_1 to T_RATE_k and the first to kth cross ratios I_RATE_1 to I_RATE_k to the association analysis unit 340.
  • the correlation analysis unit 340 may generate the target application and the first to k-th applications based on first to k-th overall ratios T_RATE_1 to T_RATE_k and first to k-th crossing ratios I_RATE_1 to I_RATE_k. First to k th association indices RI_1 to RI_k representing the degree of association between each may be determined.
  • the association analysis unit 340 may display the first to k th association indices RI_1 to RI_k through the display device.
  • the association analysis unit 340 may provide the first to k th association indices RI_1 to RI_k to an external device through a network.
  • the data server 200 collects installation log data I_LOG from each of the plurality of mobile terminals 100 in the correlation analysis system 10 between applications according to embodiments of the present invention.
  • the main server 300 receives the installation log data I_LOG of the plurality of mobile terminals 100 from the data server 200, but the present invention is not limited thereto.
  • the correlation analysis system 10 between applications may be configured such that the main server 300 performs the role of the data server 200 without separately including the data server 200.
  • the main server 300 may directly receive the installation log data I_LOG from each of the plurality of mobile terminals 100 and store it in the database 320.
  • each of the plurality of mobile terminals 100 is illustrated as a smart phone, but the present invention is not limited thereto.
  • each of the plurality of mobile terminals 100 may be any portable mobile terminal such as a tablet computer, a mobile phone, a personal digital assistant (PDA), or the like.
  • PDA personal digital assistant
  • FIG. 5 is a flowchart illustrating a method for analyzing association between applications according to an embodiment of the present invention.
  • the correlation analysis method between the applications illustrated in FIG. 5 may be performed through the correlation analysis system 10 between the applications of FIG. 1.
  • the data receiving unit 310 of the main server 300 has an installation log including an identification ID (ADID) of each of the plurality of mobile terminals 100 and a list (APP_LIST) of applications installed in each of the plurality of mobile terminals 100.
  • the data I_LOG may be received and stored in the database 320 (step S100).
  • the data server 200 receives the installation log data (I_LOG) from each of the plurality of mobile terminals 100, the data receiving unit 310 of the main server 300 from the data server 200
  • the installation log data I_LOG of the plurality of mobile terminals 100 may be received and stored in the database 320.
  • the data receiving unit 310 of the main server 300 may directly receive installation log data I_LOG from each of the plurality of mobile terminals 100 and store it in the database 320.
  • the ratio calculator 330 of the main server 300 may receive target application information T_APP indicating the target application.
  • the ratio calculator 330 may receive the target application information T_APP through an input of an administrator, or may receive the target application information T_APP from an external device through a network. have.
  • the ratio calculation unit 330 uses the list of applications (APP_LIST) included in the installation log data (I_LOG) of the plurality of mobile terminals 100 stored in the database 320 to determine the degree of association with the target application.
  • the first to k th applications to be analyzed may be determined.
  • the first to k-th applications to analyze the degree of association with the target application may be predefined in the ratio calculator 330.
  • the ratio calculator 330 may be configured to perform the first to k th applications among the plurality of mobile terminals 100 based on the installation log data I_LOG of the plurality of mobile terminals 100 stored in the database 320.
  • the first to kth overall ratios T_RATE_1 to T_RATE_k corresponding to the ratios of the mobile terminals 100 in which each is installed may be determined (step S200).
  • FIG. 6 is a flowchart illustrating an example of determining the first to kth overall ratios corresponding to the ratios of the mobile terminals in which the first to kth applications are installed among the plurality of mobile terminals in FIG. 5 (S200). .
  • the ratio calculator 330 may identify IDs corresponding to the plurality of mobile terminals 100 based on the installation log data I_LOG of the plurality of mobile terminals 100 stored in the database 320.
  • the number of fields ADID may be determined as the total number (step S210).
  • the identification ID is an identification value uniquely assigned to each mobile terminal
  • the total number may correspond to the total number of the plurality of mobile terminals 100.
  • the ratio calculator 330 may identify IDs corresponding to the mobile terminals 100 installed with the j-th application based on the installation log data I_LOG of the plurality of mobile terminals 100 stored in the database 320.
  • the number of ADIDs may be determined as the j th installation number (step S220).
  • j represents a positive integer of k or less.
  • the j th installation number may correspond to the number of mobile terminals 100 in which the j th application is installed among the plurality of mobile terminals 100.
  • the ratio calculator 330 may determine a value obtained by dividing the number of j-th installments by the total number as the j-th overall ratio T_RATE_j (step S230).
  • the j-th overall ratio T_RATE_j may represent the ratio of the mobile terminals 100 installed with the j-th application among the plurality of mobile terminals 100.
  • the ratio calculating unit 330 repeatedly performs the above-described steps S220 and S230 for each of the first to k th applications, respectively, of the plurality of mobile terminals 100.
  • the first to kth overall ratios T_RATE_1 to T_RATE_k corresponding to the ratio of the installed mobile terminals 100 may be determined.
  • the ratio calculator 330 may be configured to perform the target application based on the installation log data I_LOG of the plurality of mobile terminals 100 stored in the database 320.
  • First to k th cross ratios I_RATE_1 to I_RATE_k corresponding to the ratios of the mobile terminals 100 in which each of the first to k th applications are installed may be determined (step S300).
  • FIG. 7 illustrates an example of determining the first to k th intersection ratios corresponding to the ratio of the mobile terminals in which the first to k th applications are installed among the mobile terminals in which the target application of FIG. 5 is installed (S300).
  • the ratio calculator 330 corresponds to the mobile terminals 100 on which the target application is installed based on the installation log data I_LOG of the plurality of mobile terminals 100 stored in the database 320.
  • the number of identification IDs ADID may be determined as the target installation number (step S310).
  • the target installation number may correspond to the number of mobile terminals 100 in which the target application is installed among the plurality of mobile terminals 100.
  • the ratio calculator 330 may be configured to install the target application and the j-th application together based on the installation log data I_LOG of the plurality of mobile terminals 100 stored in the database 320.
  • the number of identification IDs (ADID) corresponding to the j th intersection may be determined (step S320).
  • the j th intersection number may correspond to the number of mobile terminals 100 in which the target application and the j th application are installed together among the plurality of mobile terminals 100.
  • the ratio calculator 330 may determine a value obtained by dividing the number of j-th crossings by the target number of installations as the j-th crossing ratio I_RATE_j (step S330).
  • the j th intersection ratio I_RATE_j may represent the ratio of the mobile terminals 100 having the j th application installed among the mobile terminals 100 having the target application installed.
  • the ratio calculating unit 330 repeatedly performs the above-described steps (S320 and S330) for each of the first to k-th applications, and the first to k-th of the mobile terminals 100 to which the target application is installed. First to k th cross ratios I_RATE_1 to I_RATE_k corresponding to the ratios of the mobile terminals 100 in which the applications are installed may be determined.
  • the ratio calculator 330 may provide the first to kth overall ratios T_RATE_1 to T_RATE_k and the first to kth cross ratios I_RATE_1 to I_RATE_k to the association analysis unit 340.
  • the correlation analysis unit 340 of the main server 300 is based on the first to k th total ratios T_RATE_1 to T_RATE_k and the first to k th intersection ratios I_RATE_1 to I_RATE_k.
  • the first to k th association indices RI_1 to RI_k representing the degree of association between the target application and each of the first to k th applications may be determined (step S400).
  • FIG. 8 is a first through k-th association index indicating an association degree between the target application and each of the first to kth applications based on the first to kth overall ratios and the first to kth intersection ratios of FIG. 5. Is a flow chart showing an example of the steps of determining them.
  • the j th overall ratio T_RATE_j represents the ratio of the mobile terminals 100 in which the j th application is installed among the plurality of mobile terminals 100, and the j th cross ratio I_RATE_j is the target application. Since the j th application ratio is greater than the j th overall ratio T_RATE_j, the target application and the target application are represented. If there is a correlation between the j th application and the j th cross ratio I_RATE_j is less than the j th overall ratio T_RATE_j, there may be an inverse correlation between the target application and the j th application. have.
  • the existence of a correlation between the target application and the j-th application means that the j-th application is installed among the mobile terminals 100 in which the target application is installed compared to the average installation ratio of the j-th application. Means greater, and that there is an inverse correlation between the target application and the j-th application among the mobile terminals 100 in which the target application is installed compared to the average installation ratio of the j-th application. It means that the ratio where the j-th application is installed is smaller.
  • the correlation analysis unit 340 may control the j-th correlation index such that the j-th correlation index RI_j has a positive value when there is a correlation between the target application and the j-th application. (RI_j) is determined, and if there is an inverse correlation between the target application and the j-th application, the j-th association index RI_j is determined such that the j-th association index RI_j has a negative value. Can be.
  • the correlation analysis unit 340 has a higher correlation value between the target application and the j-th application, and the j-th association index RI_j has a positive value.
  • the jth correlation index RI_j is determined to have a relatively large absolute value (step S410), and as the inverse correlation between the target application and the jth application is higher, the jth correlation index RI_j is negative.
  • the j-th association index RI_j may be determined to have a relatively large absolute value with a value of (step S420).
  • the association analysis unit 340 may be configured to perform the target application and the first to kth based on the first to kth total ratios T_RATE_1 to T_RATE_k and the first to kth cross ratios I_RATE_1 to I_RATE_k.
  • Various embodiments of determining the first to k th association indices RI_1 to RI_k representing the degree of association between each of the applications will be described.
  • the relevance analysis unit 340 may generate the first and second k th ratios T_RATE_1 to T_RATE_k and the first to k th intersection ratios I_RATE_1 to I_RATE_k, respectively.
  • One to k th association indices RI_1 to RI_k may be determined.
  • the correlation analysis unit 340 may determine the first to k th association indices RI_1 to RI_k based on Equation 1 below.
  • j represents a positive integer equal to or less than k
  • RI_j represents the jth association index
  • I_RATE_j represents the jth crossing ratio
  • T_RATE_j represents the jth overall ratio
  • the j-th association index RI_j is a mobile terminal in which the target application is installed. Since the difference between the ratio of the mobile terminal 100, the j-th application is installed in the number 100 and the mobile terminal 100, the j-th application is installed among the plurality of mobile terminals 100 as it is, The j th correlation index RI_j may objectively indicate a correlation or inverse correlation between the target application and the j th application.
  • the method for analyzing associations between applications may be performed without considering a subjective preference evaluation of the first to k th applications of users of the plurality of mobile terminals 100.
  • First to k-th association indices RI_1 to RI_k by estimating an association degree between the target application and each of the first to k th applications based on a list APP_LIST of applications installed in the mobile terminals 100 of FIG. Is determined.
  • the correlation analysis method between the applications according to the embodiments of the present invention may effectively improve the objectivity and accuracy of the correlation analysis between the applications.
  • the relevance analysis unit 340 may generate a first based on a ratio of each of the first to kth cross ratios I_RATE_1 to I_RATE_k for each of the first to kth overall ratios T_RATE_1 to T_RATE_k.
  • One to k th association indices RI_1 to RI_k may be determined.
  • the correlation analysis unit 340 may determine the first to k th association indices RI_1 to RI_k based on Equation 2 below.
  • j represents a positive integer equal to or less than k
  • RI_j represents the jth association index
  • I_RATE_j represents the jth crossing ratio
  • T_RATE_j represents the jth overall ratio
  • the j-th association index RI_j is the j-th overall ratio T_RATE_j. Since it is determined based on the ratio between the j th ratio (I_RATE_j) and the j th ratio (T_RATE_j) and the size of the j th intersection ratio (I_RATE_j) are similar to each other, the j association index (RI_j) is the target application. Correlation or inverse correlation between the j th application can be effectively represented.
  • both the size of the j th overall ratio T_RATE_j and the j th intersection ratio I_RATE_j may have relatively small values. Even in such a case, when the correlation analysis unit 340 determines the first to k th association indices RI_1 to RI_k based on Equation 2, the j th association index RI_j is the j th whole. Since it is determined based on the ratio between the ratio T_RATE_j and the j th intersection ratio I_RATE_j, the association analysis method between the applications according to the embodiments of the present invention effectively improves the accuracy of the association analysis between the applications. You can.
  • the correlation analysis unit 340 may determine a difference between each of the first to k-th overall ratios T_RATE_1 to T_RATE_k and each of the first to k-th cross ratios I_RATE_1 to I_RATE_k and the first.
  • the first to k th association indices RI_1 to RI_k may be determined based on a ratio of each of the first to k th cross ratios I_RATE_1 to I_RATE_k for each of the to k th total ratios T_RATE_1 to T_RATE_k. .
  • the association analysis unit 340 may determine the first to k th association indices RI_1 to RI_k based on Equation 3 below.
  • RI_j represents the jth association index
  • I_RATE_j represents the jth intersection ratio
  • T_RATE_j represents the jth overall ratio
  • ABS () is an absolute value operation
  • A_DIFF_j represents the jth absolute ratio difference
  • R_DIFF_j represents the jth relative ratio difference.
  • the j-th absolute ratio difference (A_DIFF_j) is the j-associated index (RI_j) according to [Equation 1]
  • the j-th relative ratio difference R_DIFF_j is the same as the j-th association index RI_j according to Equation 2 above. Therefore, overlapping descriptions of the j th absolute ratio difference A_DIFF_j and the j th relative ratio difference R_DIFF_j are omitted.
  • the correlation analysis unit 340 Determines the first to k th association indices RI_1 to RI_k based on Equation 3, wherein the j th association index RI_j is the j th absolute ratio difference A_DIFF_j and the j th relative ratio. It may correspond to the geometric mean of the difference R_DIFF_j.
  • the j th association index RI_j is an advantage of the correlation analysis between the target application and the j th application of the j absolute ratio difference A_DIFF_j and the j th relative ratio difference R_DIFF_j. ) May have all the advantages of the degree of association analysis between the target application and the j-th application.
  • the correlation analysis method between applications according to the embodiments of the present invention may more effectively improve the objectivity and accuracy of the correlation analysis between applications.
  • the correlation analysis unit 340 may determine a difference between each of the first to k-th overall ratios T_RATE_1 to T_RATE_k and each of the first to k-th intersection ratios I_RATE_1 to I_RATE_k. To k-th based on a ratio of each of the first to k-th crossover ratios I_RATE_1 to I_RATE_k for each of the to k-th overall ratios T_RATE_1 to T_RATE_k, and a weight having a value greater than zero and less than one. Association indexes RI_1 to RI_k may be determined.
  • the association analysis unit 340 may determine the first to k th association indices RI_1 to RI_k based on Equation 4 below.
  • RI_j represents the jth association index
  • I_RATE_j represents the jth intersection ratio
  • T_RATE_j represents the jth overall ratio
  • wt represents the weight
  • ABS () represents an absolute value operation
  • A_DIFF_j represents the j th absolute ratio difference
  • R_DIFF_j represents the j th relative ratio difference.
  • the correlation analysis unit 340 may obtain a weight (wt) through an input from the outside.
  • the correlation analysis unit 340 may obtain a weight wt by reading a weight wt stored in advance.
  • the j-th association index (RI_j) is the j th absolute ratio difference (A_DIFF_j) and the j-th applying the weight (wt) It may correspond to the weighted geometric mean of the relative ratio difference R_DIFF_j.
  • the j th association index RI_j is an advantage of the correlation analysis between the target application and the j th application of the j th absolute ratio difference A_DIFF_j and the j th relative ratio difference R_DIFF_j. ) May have all the advantages of the degree of association analysis between the target application and the j-th application.
  • the method of analyzing the association between the applications according to the embodiments of the present invention may further improve the accuracy of the analysis of the association between the applications by adjusting the weight value according to the characteristics of the target application.
  • the present invention can objectively and effectively analyze the degree of association between applications, it can be usefully used to select an advertisement target of an application for a target advertisement of the application.

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Abstract

L'invention concerne un procédé d'analyse de pertinence entre des applications comprenant : la réception de données de journal d'installation incluant des ID d'identification de multiples terminaux mobiles respectifs et une liste d'applications installées dans les multiples terminaux mobiles respectifs, et le stockage des données de journal d'installation reçues dans une base de données ; sur la base des données de journal d'installation des multiples terminaux mobiles, qui sont stockées dans la base de données, la détermination de 1 à k rapports globaux qui correspondent à des rapports des terminaux mobiles, dans lesquels 1 à k applications sont respectivement installées, parmi les multiples terminaux mobiles ; la détermination de 1 à k taux de croisement qui correspondent à des rapports des terminaux mobiles, dans lesquels les 1 à k applications sont respectivement installées, parmi des terminaux mobiles dans lesquels une application cible est installée ; et sur la base des 1 à k rapports globaux et des 1 à k taux de croisement, la détermination de 1 à k indices de pertinence qui indiquent une pertinence entre l'application cible et chacune des 1 à k applications.
PCT/KR2018/008119 2018-03-07 2018-07-18 Procédé et dispositif d'analyse de pertinence entre des applications WO2019172488A1 (fr)

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