JP5348619B2 - Information analysis processing system and information analysis processing method - Google Patents

Description

  The present invention relates to an information analysis processing system and an information analysis processing method for analyzing consumer trends.

  Conventionally, techniques for analyzing consumer trends have been proposed. For example, in the prior art described in Patent Document 1, a user profile representing a user's interest as each consumer is held in a user profile database. Then, for example, an information provider such as an advertiser uses the information provider terminal to input a keyword representing the characteristics of the product to be advertised. Then, the server extracts a group 1 that is a user group as a unit that matches the keyword input by the information provider based on the user profile database. Next, the server selects a group 2 which is a user group having an interest similar to the extracted group 1 based on the user profile database. Next, the server discovers interests and the like possessed by many users in the same group from the groups 1 and 2 and records them as a knowledge system in the knowledge system database.

  Then, the server transmits the above result to the information provider terminal, visualizes it, and displays it. Thereby, the information provider can confirm on the screen a user group who may be interested in the product to be advertised by only inputting a keyword or the like expressing the advertisement product.

JP 2001-75972 A

  In the above prior art, a unit having higher relevance to the operation input content of the operator is displayed at the center of the screen, and as the relevance becomes lower, the display position of the unit is displayed on the screen so as to move away from the center of the screen. . Therefore, in this case, there is a case where the unit is not displayed on the screen for the unit having low relevance to the operation input content of the operator. As a result, the operator may not be able to recognize which unit is less relevant.

  SUMMARY OF THE INVENTION An object of the present invention is to provide an information analysis processing system and information capable of reliably displaying a unit having low relevance to an operation input by an operator and recognizing which unit has low relevance. It is to provide an analysis processing method.

In order to achieve the above object, an information analysis processing system according to a first aspect of the invention includes a first signal input means for inputting a first operation signal for designating product-related identification information related to a product to be analyzed, A consumer database storing consumption history information in which identification information of the product is associated with consumption behavior histories of a plurality of consumers for the product, accessing the consumer database, and designated by the first operation signal Identification information acquisition means for acquiring identification information of each of a plurality of consumers who performed consumption behavior on a predetermined product corresponding to the product related identification information, and identification information of the plurality of consumers by clustering executed in advance A clustering database storing clustering information in which a plurality of units are associated with each other, and accessing the clustering database. The number of consumers whose identification information has been acquired by the identification information acquisition means is counted by the consumer counting means in a unit display area corresponding to each unit, and a consumer counting means for counting each unit. Image generating means for generating image information for displaying at least one identifier corresponding to the number of consumers belonging to the unit , wherein the image generating means connects the plurality of unit display areas to each other. It is characterized by having lattice image generation means for generating image information to be displayed in unit lattices of the same size and to arrange and display the plurality of unit lattices in a hexagonal lattice shape .

  In the first invention of the present application, identification information of a plurality of products and consumption behavior histories of a plurality of consumers for the products are associated in advance and stored in the consumer database as consumption history information. The information analysis processing system according to the first aspect of the present application has first signal input means. When the operator operates appropriate operation means and specifies product related identification information related to the product to be analyzed, the first signal input means inputs a first operation signal corresponding to the operation. When this first operation signal is input, the identification information acquisition means accesses the consumer database, identifies a plurality of consumers who have performed consumption behaviors on the predetermined product corresponding to the product related identification information, The identification information of the plurality of consumers is acquired.

  In the first invention of the present application, clustering is executed in advance, and the identification information of a plurality of consumers and a plurality of units are associated by the clustering and stored as clustering information in a clustering database. When consumers who have consumed a specific product are identified as described above, the consumer counting means accesses the clustering database, and the number of consumers whose identification information has been acquired by the identification information acquisition means is determined for each unit. Count. Thus, the number of consumers who have consumed a specific product is counted for each unit. The image generation means generates image information according to the count result. Accordingly, an appropriate display unit using the image information can display an image of the number of consumers counted for each unit by using at least one identifier.

Thereby, regardless of whether the number of counted consumers is large or small, it is possible to visually represent the number of corresponding consumers in all units. Therefore, unlike a method of displaying a unit highly relevant to the operation input content of the operator at the center of the screen, a unit having a low relevance to the operation input of the operator can also be reliably displayed on the screen. As a result, the operator can surely recognize which unit is less relevant. Further, the image generation means displays the plurality of unit display areas in unit lattices having the same size, and generates image information for displaying the plurality of unit lattices arranged in a hexagonal lattice shape. Unlike the technique of arranging four units at the four vertices of a square by arranging units that are similar to each other at adjacent positions in the hexagonal lattice by having generation means, the similarity can be expressed in an easy-to-understand manner. Can do.

  The information analysis processing system according to a second aspect of the present invention further includes a second operation input means for inputting a second operation signal for specifying a period range in which the product is consumed, which is an analysis processing target, in the first invention. The identification information acquisition means accesses the consumer database and, for a product corresponding to the product related identification information specified by the first operation signal, within a period range specified by the second operation signal. The identification information of each of the plurality of consumers who performed the consumption behavior is acquired.

  In the second invention of the present application, when the operator operates a suitable operation means and designates a period during which the product to be analyzed is consumed, the second operation for the second signal input means to specify the designated period range. Input the signal. In this way, it is possible to count how many consumers have consumed a specific product in a specific period for each unit, and to express the size of the number of consumers of the product for each unit in an easy-to-understand manner. Can do.

Third information analysis processing system of the present invention, said Oite the first invention, the identification information acquiring means, corresponding to the singing history as a consumer action history for the identified information and the singing music of singing songs as the product Identification of each of a plurality of consumers who accessed the consumer database storing the attached singing history information and performed singing on a predetermined singing song corresponding to the product-related identification information specified by the first operation signal It is characterized by acquiring information.

  As a result, it is possible to count how many consumers who sing a specific song song are included in each unit, and to express the size of the number of singers of the song song for each unit in an easy-to-understand manner. .

Fourth information analysis process system of the present invention is, in the third invention, the first signal input means, as said product-related identification information, said designating singer identification information corresponding to the singing music analysis processed first One operation signal is input.

  Thereby, when an operator inputs singer identification information of a specific singer with an appropriate operation means, the number of singers for the singer's music is expressed in an easily understandable manner for each unit. Further, the operator can surely recognize which unit is not interested in or less interested in the music of the singer.

In order to achieve the above object, an information analysis processing method according to a fifth aspect of the present invention includes a signal input procedure for inputting an operation signal specifying product-related identification information related to a product to be analyzed, and identification of a plurality of products. A consumer database storing consumption history information in which information and consumption behavior histories of a plurality of consumers for the product are associated is accessed, and a predetermined product corresponding to the product related identification information specified by the operation signal is accessed. The identification information acquisition procedure for acquiring the identification information of each of the plurality of consumers who performed the consumption action on the consumer, and the clustering information in which the identification information of the plurality of consumers and the plurality of units are associated by clustering executed in advance The stored clustering database is accessed, and the number of consumers whose identification information has been acquired in the identification information acquisition procedure is determined for each unit. And at least one identifier corresponding to the number of the consumers belonging to the unit counted in the consumer counting procedure is displayed in a unit display area corresponding to each unit. An image generation procedure for generating image information , wherein the image generation means displays each of the plurality of unit display areas in unit grids of the same size, and the unit grids are in a hexagonal grid pattern. And grid image generating means for generating image information to be arranged and displayed .

In the fifth invention of this application, when the operator operates appropriate operation means and specifies product related identification information related to the product to be analyzed, an operation signal corresponding to the operation is input in the signal input procedure. When this operation signal is input, the consumer database is accessed in the identification information acquisition procedure, and a plurality of consumers who have performed a consumption action on a predetermined product corresponding to the product-related identification information are identified, Identification information of the plurality of consumers is acquired.

  When consumers who have consumed a specific product are identified in this way, the clustering database is accessed in the consumer counting procedure, and the number of consumers whose identification information has been acquired in the identification information acquisition procedure is determined for each unit. Will be counted. Thus, the number of consumers who have consumed a specific product is counted for each unit. In the image generation procedure, image information is generated according to the count result. Accordingly, the image information can be used to display an image of the counted number of consumers for each unit using at least one identifier.

  Thereby, regardless of whether the number of counted consumers is large or small, it is possible to visually represent the number of corresponding consumers in all units. Therefore, unlike a method of displaying a unit highly relevant to the operation input content of the operator at the center of the screen, a unit having a low relevance to the operation input of the operator can also be reliably displayed on the screen. As a result, the operator can surely recognize which unit is less relevant.

  According to the present invention, it is possible to reliably display on the screen a unit having low relevance to the operation input of the operator, and to reliably recognize which unit has low relevance.

1 is a system configuration diagram illustrating an overall configuration of an information analysis processing system according to an embodiment of this invention. It is a table | surface which represents an example of the memory content of a music master database conceptually. It is a table | surface which represents an example of the memory content of a singer master database conceptually. It is a table | surface which represents an example of the memory content of a song history database conceptually. It is a table | surface which represents an example of the memory content of a user profile database notionally. It is explanatory drawing showing an example of the screen for analysis displayed on the display connected to PC terminal for analysts. It is a sequence diagram showing the control procedure by the information analysis processing method performed between a PC terminal for analysts and a WEB server. It is a table | surface which represents an example of the memory content of a temporary table conceptually. It is a flowchart showing the detailed procedure of step SB200.

  Hereinafter, an embodiment of the present invention will be described with reference to the drawings.

  The overall configuration of the information analysis processing system of this embodiment will be described with reference to FIG.

  In FIG. 1, the information analysis processing system 1 includes a DB server 100, a calculation PC terminal 200, a WEB server 300, and an analyzer PC terminal 400.

  The DB server 100 includes a control unit 101, a communication control unit 103, and a storage unit 110.

  The control unit 101 includes a CPU (not shown) and a memory such as a RAM and a ROM. The control unit 101 executes various programs stored in advance in the storage unit 110 while using the temporary storage function of the RAM. As a result, the entire DB server 100 is controlled.

  The communication control unit 103 controls information communication with the calculation PC terminal 200 via a network NW1 such as a local area network (LAN). At the same time, control of information communication with the WEB server 300 via the network NW2 such as a LAN is performed.

  The storage unit 110 is configured by, for example, a hard disk drive (HDD). The storage unit 110 includes an OS storage area 111, an RDBMS storage area 112, and a database storage area 113.

  The OS storage area 111 stores a predetermined operating system (OS). The OS is software that manages the entire computer system.

  The RDBMS storage area 112 stores a predetermined Relational DataBase Management System (RDBMS). RDBMS is software that manages a so-called relational database.

  The database storage area 113 includes a member database (not shown), a music master database 1131 (see FIG. 2 described later), a singer master database 1132 (see FIG. 3 described later), and a singing history database 1133 as a consumer database (described later). 4) and a user profile database 1134 (see FIG. 5 described later) as a clustering database is stored.

  In the member database, member information of a plurality of consumers registered as members related to accompaniment reproduction work of singing songs, in other words, karaoke work is stored. Member information includes consumer identification information such as UID, gender, date of birth, and the like.

  The DB server 100 having the above configuration is connected to the calculation PC terminal 200 via the network NW1 and is connected to the WEB server 300 via the network NW2.

  A display 220, a keyboard 221, and a mouse 222 are connected to the calculation PC terminal 200. The calculation PC terminal 200 includes a control unit 201, a communication control unit 202, an output control unit 203, an input control unit 204, and a storage unit 210.

  The control unit 201 includes a CPU (not shown) and a memory such as a RAM and a ROM. The control unit 201 executes various programs stored in advance in the storage unit 210 while using the temporary storage function of the RAM. As a result, the entire calculation PC terminal 200 is controlled.

  The communication control unit 202 controls information communication performed with the DB server 100 via the network NW1.

  The output control unit 203 performs control related to the output of the video signal to the display 220. The input control unit 204 performs control related to input of information via the keyboard 221 and the mouse 222.

  The storage unit 210 is composed of, for example, an HDD. The storage unit 210 includes an OS storage area 211 in which a predetermined OS is stored, and a program storage area 212 in which a user profile determination processing program is stored.

  The user profile determination processing program is a program for causing the control unit 201 to execute processing for generating clustering information (described later) stored in the user profile database 1134 of the DB server 100. In the present embodiment, the control unit 201 executes predetermined clustering according to the user profile determination processing program at a predetermined interval, for example, once / month. Note that the clustering is a method of automatically classifying a plurality of data without an external standard using a clustering method such as a well-known K-means method or a Self Organizing Map (SOM) method, or an algorithm thereof. is there.

  On the other hand, the WEB server 300 includes a control unit 301, communication control units 302 and 303, and a storage unit 310.

  The control unit 301 includes a CPU and a memory such as a RAM and a ROM (not shown). The control unit 301 executes various programs stored in advance in the storage unit 310 while using the temporary storage function of the RAM. Thus, the entire WEB server 300 is controlled.

  The communication control unit 302 controls information communication performed with the DB server 100 via the network NW2. The communication control unit 303 controls information communication with the analyzer PC terminal 400 via a network NW3 such as a wide area network (WAN).

  The storage unit 310 is composed of, for example, an HDD. The storage unit 310 includes an OS storage area 311 in which a predetermined OS is stored, a program storage area 312 in which a WEB server program is stored, and a preference map image storage area 313.

  The WEB server program is a program for causing the control unit 301 to execute processing for providing a display of an object such as Hyper Text Markup Language (HTML) or an image to a predetermined web browser.

  In the preference map image storage area 313, image information (details will be described later) generated by the control unit 301 is stored.

  The WEB server 300 having the above configuration is connected to the analyzer PC terminal 400 via the network NW3.

  A display 420, a keyboard 421, and a mouse 422 are connected to the analyzer PC terminal 400. The analyzer PC terminal 400 includes a control unit 401, a communication control unit 402, an output control unit 403, an input control unit 404, and a storage unit 410.

  The control unit 401 includes a CPU (not shown) and a memory such as a RAM and a ROM. The control unit 401 executes various programs stored in advance in the storage unit 410 while using the temporary storage function of the RAM. As a result, the entire analyzer PC terminal 400 is controlled.

  The communication control unit 402 controls information communication with the WEB server 300 via the network NW3.

  The output control unit 403 performs control related to the output of the video signal to the display 420. The input control unit 404 performs control related to information input via the keyboard 421 and the mouse 422. The input control unit 404 functions as a first signal input unit and a second signal input unit described in each claim.

  The storage unit 410 is composed of, for example, an HDD. The storage unit 410 includes an OS storage area 411 in which a predetermined OS is stored, and a web browser storage area 412 in which a predetermined web browser is stored.

  FIG. 2 shows an example of the contents stored in the music master database 1131.

  As shown in FIG. 2, in the music master database 1131, a music ID that is identification information of a plurality of song songs and a singer ID that is identification information of a singer corresponding to the song music are stored in association with each other. Yes. Singing music (hereinafter abbreviated as “music”) corresponds to a product.

  FIG. 3 shows an example of the contents stored in the singer master database 1132.

  As shown in FIG. 3, the singer master database 1132 stores a plurality of singer IDs and singer names in association with each other. The singer name corresponds to singer identification information corresponding to the singing song and also corresponds to product related identification information related to the product.

  FIG. 4 shows an example of the contents stored in the singing history database 1133.

  As shown in FIG. 4, the singing history database 1133 stores singing history information in which music IDs of a plurality of songs are associated with a plurality of consumer singing histories for the music. The singing history corresponds to the consumption behavior history. Singing history information corresponds to consumption history information.

  The singing history information includes the UID of the consumer who sang the song, the singing date and time information on the date and time when the song was sung, and the song ID of the song. Note that the fact that the consumer has sung the music, that is, that the consumer has sung the music corresponds to the consumer performing a consumption action on the music.

  FIG. 5 shows an example of the contents stored in the user profile database 1134.

  As illustrated in FIG. 5, the user profile database 1134 stores clustering information generated by clustering executed in advance by the control unit 201 of the calculation PC terminal 200. Clustering information is information that associates UIDs of a plurality of consumers with a plurality of units having different preferences or consumption time periods (specifically, unit IDs that are identification information of a plurality of units; the same applies hereinafter) by clustering. It is. Note that the number of the units is determined in advance.

  That is, in the user profile database 1134, UIDs of a plurality of consumers and unit IDs of units to which the consumers belong are associated and stored. In this embodiment, based on the singing history information of a plurality of consumers for a plurality of songs stored in the singing history database 1133 of the DB server 100, the UIDs of the plurality of consumers are clustered into a plurality of units. Yes.

  Note that the data used for clustering is not limited to the singing history information of a plurality of consumers for a plurality of songs stored in the singing history database 1133. For example, based on purchase history information as consumption history information of a plurality of consumers for an article as a plurality of products, the UIDs of the plurality of consumers may be clustered into a plurality of units.

  Here, in the present embodiment, when an operator activates a predetermined application installed in advance on the analyzer PC terminal 400 using the keyboard 421 and the mouse 422 connected to the analyzer PC terminal 400. A predetermined analysis screen is displayed on the display 420 connected to the analyzer PC terminal 400.

  FIG. 6 shows an example of an analysis screen displayed on the display 420 connected to the analyzer PC terminal 400.

  As shown in FIG. 6, the analysis screen P includes a singer name input box T1, a period input box T2, a result image display area T3, and an analysis start button S. The singer name input box T1 is a column in which the singer name corresponding to the music to be analyzed is input. The period input box T2 is a column in which a period range desired to be analyzed is input. The result image display area T3 is an area in which a result image of the analysis process is displayed. The analysis start button S is a button for starting analysis processing.

  When the analysis screen P is displayed on the display 420, the operator operates the mouse 422 to select the singer name input box T1 as an input destination by the keyboard 421. Then, by operating the keyboard 421, the name of the singer corresponding to the music to be analyzed is input to the singer name input box T1. In this example, “Artist1” is input. Then, the input control unit 404 (see FIG. 1) of the analyst's PC terminal 400 designates the singer name corresponding to the music to be analyzed corresponding to the operation of the keyboard 421 input to the singer name input box T1. Input an operation signal. This operation signal corresponds to the first operation signal and the operation signal described in each claim. The procedure for inputting the operation signal corresponds to the signal input procedure described in each claim.

  The operator operates the mouse 422 to select the period input box T2 as an input destination using the keyboard 421. Then, the keyboard 421 is operated to input a period range to be analyzed in this period input box T2. In this example, “2009/01/01 to 2009/12/31” is input. Note that the period range is not limited to “year / month / day” units as in this example, and may include time units. Then, the input control unit 404 inputs an operation signal for specifying a period range in which the music is sung, which is an analysis processing target, corresponding to the operation of the keyboard 421 input to the period input box T2. This operation signal corresponds to the second operation signal described in each claim. The period range in which the music is sung corresponds to the period range in which the product is consumed.

  When the operator completes the input of the singer name and the period range, the operator operates the mouse 422 and clicks the analysis start button S. Thereby, an analysis instruction signal is output to the WEB server 300 via the network NW3, and the WEB server 300 performs an analysis process based on the singer name and period range corresponding to the music to be analyzed.

  In the analysis process in the WEB server 300, the singing history database 1133 of the DB server 100 is accessed, and each of a plurality of consumers who sang the music corresponding to the specified singer name within the specified period range. A UID is obtained. Thereafter, the user profile database 1134 of the DB server 100 is accessed, and the number of consumers who have obtained the UID is counted for each unit described above. Then, image information based on the count result is generated and output to the analyzer PC terminal 400 via the network NW3. As a result, an image corresponding to the image information is displayed as a result image of the analysis process in the result image display region T3 of the analysis screen P displayed on the display 420 connected to the analyzer PC terminal 400. The

  As shown in FIG. 6, in the result image display area T3 of the analysis screen P, an image including a plurality of unit display areas US corresponding to each unit and an X mark M is obtained as a result image of the analysis process. Is displayed. The x mark M corresponds to an identifier.

  The plurality of unit display areas US are respectively displayed by circular unit grids having the same size. Along with this, the plurality of unit cells are arranged and displayed in a hexagonal lattice pattern. In each unit display area US, the unit ID of the corresponding unit is written. In this example, as an example, 36 unit display areas US corresponding to 36 units are shown.

  At this time, the units similar to each other are arranged such that the corresponding unit display areas US are adjacent to each other. That is, in this example, for a unit with unit ID = 8, for example, units with unit ID = 1, 2, 7, 9, 13, 14 adjacent to the unit are similar units.

  The x mark M is displayed in the unit display area US. This X mark M corresponds to the number of consumers belonging to the unit counted for each unit. Moreover, in this example, the magnitude of the number of consumers for each unit is represented by a density of at least one X mark M. That is, as the number of consumers belonging to the unit increases, the number of X marks M displayed in the corresponding unit display area US increases. Conversely, as the number of consumers belonging to the unit decreases, the number of crosses M displayed in the corresponding unit display area US decreases. Note that the same number of X marks M as the number of consumers belonging to a unit may be displayed in the unit display area US corresponding to the unit.

  The unit display area is not limited to unit grids having the same size as described above. For example, the unit display area may be displayed as a bar graph or a pie graph. The identifier is not limited to the above x mark M. For example, the identifier may be expressed by a numerical value, a color distribution, or the like corresponding to the number of consumers belonging to the counted unit.

  The control procedure by the information analysis processing method in this embodiment performed between PC terminal 400 for analysts and WEB server 300 is demonstrated using FIG. In FIG. 7, each procedure is basically shown as a time series change from the upper side to the lower side in the figure.

  In FIG. 7, when a predetermined application installed in advance on the analyzer PC terminal 400 is activated, first, in step SA100, the control unit 401 of the analyzer PC terminal 400 displays the display 420 via the output control unit 403. A control signal is output to display the analysis screen P. At this time, the singer name input box T1, the period input box T2, and the result image display area T3 in the analysis screen P are blank.

  Thereafter, in step SA110, the control unit 401 of the analyzer PC terminal 400 designates the singer name corresponding to the music to be analyzed corresponding to the operation of the keyboard 421 input to the singer name input box T1 by the operator. An operation signal to be input is input via the keyboard 421 and the input control unit 404. The singer name designated by the input operation signal is X.

  Then, the process proceeds to step SA120, in which the control unit 401 of the analyzer PC terminal 400 is the period during which the music to be sung is analyzed, corresponding to the operation of the keyboard 421 input to the period input box T2 by the operator. An operation signal specifying the range is input via the keyboard 421 and the input control unit 404. A period range specified by the input operation signal is D.

  Thereafter, in step SA130, the control unit 401 of the analyzer PC terminal 400 determines whether or not the analysis start button S is clicked via the mouse 422. The determination is not satisfied until the analysis start button S is clicked, and loops and waits. If the analysis start button S is clicked, the determination is satisfied, and the routine goes to Step SA140.

  In step SA140, the control unit 401 of the analyzer PC terminal 400 determines the singer name = X specified by the operation signal input in step SA110 and the period specified by the operation signal input in step SA120. An analysis instruction signal based on the range = D is output to the WEB server 300 via the communication control unit 402 and the network NW3.

  Thus, the control unit 301 of the WEB server 300 inputs the analysis instruction signal via the network NW3 and the communication control unit 303. Then, in step SB100, the control unit 301 of the WEB server 300 accesses the singer master database 1132 (see FIG. 3) of the DB server 100 via the communication control unit 302 and the network NW2. Based on the input analysis start signal, the singer ID associated with the singer name = X is acquired using the singer name = X designated in step SA110 as a key. The acquired singer ID is assumed to be X ′.

  Then, the process proceeds to step SB110, and the control unit 301 of the WEB server 300 accesses the singing history database 1133 (see FIG. 4) of the DB server 100 via the communication control unit 302 and the network NW2. Then, based on the input analysis start signal, the singing date and time is within the period range = D specified in step SA120, and the singer ID matches the singer ID = X ′ acquired in step SB100. UID included in all singing history information is acquired. That is, in this step, the control unit 301 accesses the singing history database 1133, and the singer name is within a predetermined music, specifically, the period range = D specified by the operation signal specifying the period range. The UID of each of a plurality of consumers who sang a song corresponding to the singer name = X designated by the operation signal designating “X” is acquired. This step functions as identification information acquisition means described in each claim and corresponds to an identification information acquisition procedure.

  The data used in step SB110, that is, the singing history information stored in the singing history database 1133 is not necessarily the same data as the data used in the previously executed clustering. That is, in this step SB110, the singing history information including the singing history for the music that has not been put on the market when the clustering is executed may be used. As a result, when clustering is executed, it is possible to cope with unknown data.

  Thereafter, in step SB120, the control unit 301 of the WEB server 300 accesses the user profile database 1134 (see FIG. 5) of the DB server 100 via the communication control unit 302 and the network NW2. Then, the UID acquired in step SB110 is classified for each unit ID, and the number of UIDs, in other words, the number of consumers whose UIDs are acquired in step SB110 is counted for each unit. This step functions as a consumer counting means described in each claim and corresponds to a consumer counting procedure.

  Then, in step SB130, the control unit 301 of the WEB server 300 tabulates the count result in step SB120 and stores a memory such as a RAM in the control unit 101 of the DB server 100 as a temporary table (see FIG. 8 described later). Remember me.

  Thereafter, in step BS200, the control unit 301 of the WEB server 300 performs analysis processing on the result image display area T3 of the analysis screen P displayed on the display 420 connected to the analyzer PC terminal 400 in step SA100. An image information generation process for generating image information to be displayed as a result image is executed. This detailed content will be described later with reference to FIG. 9, but in this step, the control unit 301 is placed in the unit display area US and is a consumer belonging to the unit counted for each unit in step SB120. The image information for displaying the above-mentioned x mark corresponding to the number of is generated.

  Then, the process proceeds to step SB140, and the control unit 301 of the WEB server 300 outputs the image information generated in step SB200 to the analyzer PC terminal 400 via the communication control unit 303 and the network NW3.

  Thereby, the control unit 401 of the analyzer PC terminal 400 inputs the image information via the network NW 3 and the communication control unit 402. Then, the control unit 401 of the analyzer PC terminal 400 outputs a control signal to the display 420 via the output control unit 403 in step SA150. Then, an image corresponding to the input image information is displayed as a result image of the analysis process in the result image display area T3 of the analysis screen P displayed on the display 420 in step SA100. Thereafter, this flow is terminated.

  In the present embodiment, as described above, the image information is generated using clustering information generated by clustering executed in advance. Therefore, the processing time can be shortened compared to the case where clustering is performed each time to generate clustering information and the image information is generated using the clustering information.

  FIG. 8 shows an example of the temporary table. As shown in FIG. 8, for each unit, the unit ID of the unit and the number of consumers belonging to the unit counted in step SB120 in FIG. 7 are stored in the temporary table.

  The detailed procedure of step SB200 in FIG. 7 will be described with reference to FIG.

  In FIG. 9, first, in step SB205, the control unit 301 generates image information in an initial state. In this example, the control unit 301 displays the background color in white, displays the plurality of unit display areas US (see FIG. 6) with circular unit lattices having the same size, and displays the plurality of unit display areas US. Image information is generated to display unit lattices arranged in a hexagonal lattice.

  Thereafter, in step SB210, the control unit 301 detects the number of records in the temporary table generated in step SB130 of FIG. The detected number of records is C. A “record” is a unit of data constituting a table or a database. For example, in the temporary table shown in FIG. 8, the data of the unit ID and the number of consumers related to one unit, that is, the data for one row is one record.

  In step SB215, the control unit 301 sets the value of the variable i for counting the number of records in the temporary table to 1.

  Thereafter, in step SB220, the control unit 301 obtains the i-th data stored in the temporary table, that is, data indicating the unit ID and the number of consumers counted in step SB120 of FIG. To do. The acquired data is R.

  Then, the process proceeds to step SB225, and the control unit 301 determines whether or not the number of consumers represented by the data indicating the number of consumers included in the data = R acquired in step SB220 is zero. If the number of consumers is 0, the determination is satisfied and the routine goes to Step SB265 described later. On the other hand, if the number of consumers is not 0, the determination is not satisfied and the routine goes to Step SB230.

  In step SB230, the control unit 301 refers to the xy coordinates corresponding to each unit stored in advance in an appropriate area of the storage unit 310 of the WEB server 300, and the data acquired in step SB220 = R The xy coordinates corresponding to the unit ID included in are acquired. The value of the x coordinate of the acquired xy coordinates is U, and the value of the y coordinate is V. The xy coordinates corresponding to each unit stored in an appropriate area of the storage unit 310 are the coordinates corresponding to the position of each unit display area US in the initial state image information generated in step SB205. It is.

  Thereafter, in step SB235, the control unit 301 sets the value of the variable j for counting the number of consumers represented by the data indicating the number of consumers included in the data = R acquired in step SB220 to 0. Set.

  Then, the process proceeds to step SB240, and the control unit 301 outputs a control signal to a random number generator (not shown) to generate two random numbers within a predetermined range. These two generated random numbers are designated as B1 and B2, respectively.

  Thereafter, in step SB245, the control unit 301 adds the random number = B1 generated in step SB240 to the x coordinate value U of the xy coordinates (U, V) acquired in step SB230, thereby obtaining the value of the x coordinate. Is set to A. At the same time, the random number = B2 generated in step SB240 is added to the y coordinate value V of the xy coordinates (U, V) acquired in step SB230, and the y coordinate value is set to B.

  Then, the process proceeds to step SB250, and the control unit 301 moves the above X mark M (see FIG. 6) to the position of the xy coordinates (A, B) set in step SB245 in the image information generated at this time. Generate image information plotting. That is, in this step, the control unit 301 generates image information for displaying the mark M in the unit display area US corresponding to the unit ID included in the data = R acquired in step SB220. By repeating this step, it is possible to generate image information that expresses the size of the number of consumers belonging to the unit counted in step SB120 in FIG.

  Thereafter, in step SB255, the control unit 301 adds 1 to the value of the variable j, and proceeds to step SB260.

  In step SB260, the control unit 301 determines whether the value of the variable j is equal to the number of consumers represented by the data indicating the number of consumers included in the data = R acquired in step SB220. To do. In other words, data indicating the number of consumers included in the data = R acquired in step SB220 is displayed in the unit display area US corresponding to the unit ID included in the data = R acquired in step SB220. It is determined whether or not image information in which the same number of crosses M as the number of consumers to be represented is plotted is generated. Until the value of the variable j becomes equal to the number of consumers represented by the data indicating the number of consumers included in the data = R, the determination is not satisfied and the process returns to step SB240 and the same procedure is repeated. When the value of the variable j becomes equal to the number of consumers represented by the data indicating the number of consumers included in data = R, the determination is satisfied and the routine goes to Step SB265.

  In step SB265, the control unit 301 adds 1 to the value of the variable i, and proceeds to step SB270.

  In step SB270, the control unit 301 determines whether or not the value of the variable i is larger than the number of records detected in step SB210 = C. If i ≦ C, the determination is not satisfied and the routine returns to step SB220 and the same procedure is repeated. On the other hand, if i> C, the determination is satisfied, and the image information generated at this time is stored in a memory such as a RAM in the control unit 301 and stored in the preference map image storage area 313. Store this and finish this routine.

  In the above, all the procedures in step SB200, that is, steps SB205 to SB270 function as image generation means described in each claim and correspond to an image generation procedure. Of these Steps SB205 to SB270, Step SB205 functions as a lattice image generating means.

  As described above, in the present embodiment, the singing history information is stored in advance in the singing history database 1133 of the DB server 100 (see FIG. 4). Then, when the operator operates the keyboard 421 and specifies product-related identification information related to the music to be analyzed, in the above example, the singer name corresponding to the music, the input control unit 404 performs the operation. Input the corresponding operation signal. And when the operation signal which designates this singer name is input, the control part 301 of the WEB server 300 accesses the said singing history database 1133, and performed the singing with respect to the predetermined music corresponding to the said designated singer name. The plurality of consumers are specified, and the UIDs of the plurality of consumers are acquired (see step SB110 in FIG. 7).

  In this embodiment, clustering is performed in advance, and clustering information generated by the clustering is stored in the user profile database 1134 of the DB server 100 (see FIG. 5). And if the consumer who sang a specific music is specified as mentioned above, the control part 301 of the WEB server 300 will access the said user profile database 1134, and will display the number of consumers from whom the said UID was acquired. Counting is performed for each unit (see step SB120 in FIG. 7). This counts how many consumers who sing a specific piece of music are included in each unit. Then, the control unit 301 of the WEB server 300 generates image information according to the count result (see step SB200 in FIG. 7), and outputs the generated image information to the analyzer PC terminal 400. As a result, the display 420 connected to the analyzer PC terminal 400 using the image information can display an image of the number of consumers counted for each unit by the X mark M. .

  Thereby, regardless of whether the number of counted consumers is large or small, it is possible to visually represent the number of corresponding consumers in all units. Therefore, unlike a method of displaying a unit highly relevant to the operation input content of the operator at the center of the screen, a unit having a low relevance to the operation input of the operator can also be reliably displayed on the screen. As a result, the operator can surely recognize which unit is less relevant.

  In the present embodiment, in particular, when the operator operates the keyboard 421 and designates a period range during which the music is sung, which is an analysis processing target, the input control unit 404 identifies the designated period range. Input the signal. Moreover, the control part 301 of the WEB server 300 accesses the said song history database 1133 which memorize | stored the song history information which matched music ID and the song history with respect to the said music. And UID of each of several consumers who performed the singing with respect to the music corresponding to the said singer name specified within the above-mentioned specified period range is acquired. Thus, it is possible to count how many consumers who sing a specific musical piece in a specific period are included in each unit. As a result, the size of the number of singers of the music for each unit can be expressed visually and easily.

  In the present embodiment, in particular, the input control unit 404 inputs an operation signal for designating a singer name corresponding to the music to be analyzed. Thereby, when an operator inputs the singer's name of a specific singer with the keyboard 421, the number of the singer with respect to the music of the said singer is expressed visually clearly for every unit. Further, the operator can surely recognize which unit is not interested in or less interested in the music of the singer.

  In the present embodiment, in particular, the control unit 301 of the WEB server 300 displays the plurality of unit display areas US in unit lattices having the same size, and arranges the plurality of unit lattices in a hexagonal lattice shape. The image information to be displayed is generated (see step SB205 in FIG. 9). Thereby, unlike the method of arranging four units at four vertices of a square by arranging units similar to each other at adjacent positions in the hexagonal lattice, the similarity can be easily expressed. In particular, the control unit 301 generates image information that expresses the number of consumers belonging to the unit counted in step SB120 in FIG. Thereby, in each unit, the counted number of consumers can be expressed visually and easily for the operator.

  The present invention is not limited to the above-described embodiment, and various modifications can be made without departing from the spirit and technical idea of the present invention. Hereinafter, such modifications will be described.

(1) When the product to be analyzed is an article In the above embodiment, the case has been described as an example where the product to be analyzed is a music piece. However, the present invention is not limited to this. It may be an article.

  In this case, the operator operates the keyboard 421 to input a product name corresponding to the product as product related identification information related to the product to be analyzed. Then, the input control unit 404 inputs an operation signal for designating a product name corresponding to the article to be analyzed, corresponding to the operation of the keyboard 421. Further, the operator operates the keyboard 421 to input a period range in which the article is consumed, that is, a period range in which the article is purchased, which is an analysis processing target. Then, the input control unit 404 inputs an operation signal corresponding to the operation of the keyboard 421 and specifying the period range during which the article is purchased, which is an analysis processing target.

  In addition, when an operation signal specifying the product name and an operation signal specifying the period range are input, an analysis instruction signal based on these operation signals is output to the WEB server 300. Then, the control part 301 of the WEB server 300 accesses the database which memorize | stored the purchase history information which matched the identification information of several goods, and the purchase history of several consumers with respect to the said goods as a consumer database. The purchase history corresponds to a consumption behavior history. The purchase history information corresponds to consumption history information.

  And the control part 301 acquires UID of each of several consumers who performed the purchase action as a consumption action with respect to the goods corresponding to the said designated product name within the specified period range. Thereafter, as in the above embodiment, the control unit 301 accesses the user profile database 1134, counts the number of consumers for which the UID has been acquired for each unit, and determines image information according to the count result. Is generated.

  In the present modification, the product name corresponding to the product is specified as the product-related identification information related to the product to be analyzed. However, the present invention is not limited to this, and the Japan Article Number ( (JAN) code, product manufacturer name, etc. may be designated.

  Also by this modification, the same effect as the above-mentioned embodiment is acquired.

  Note that the system configuration of the information analysis processing system 1 described above is an example, and the information analysis processing system may be realized with other system configurations. Furthermore, each process such as a process related to the generation of image information may be executed by a device different from the above embodiment or the modification of (1).

  In addition, in the above, the arrow shown in FIG. 1 shows an example of the signal flow, and does not limit the signal flow direction.

  The flowcharts shown in FIG. 7 and FIG. 9 do not limit the present invention to the procedure shown in the above-mentioned flow, and the addition / deletion of the procedure or the change of the order within the scope of the gist and technical idea of the invention. May be.

  In addition to those already described above, the methods according to the above-described embodiments and modifications may be used in appropriate combination.

  In addition, although not illustrated one by one, the present invention is implemented with various modifications within a range not departing from the gist thereof.

1 Information Analysis Processing System 100 DB Server 1133 Singing History Database (Consumer Database)
1134 User profile database (clustering database)
200 PC terminal for calculation 300 WEB server 301 Control unit 400 PC terminal for analyst 401 Control unit 404 Input control unit (first signal input unit, second signal input unit)
420 Display 421 Keyboard M × mark (identifier)
US unit display area

Claims (5)

First signal input means for inputting a first operation signal for designating product related identification information related to a product to be analyzed;
A consumer database storing consumption history information in which identification information of a plurality of products is associated with consumption behavior histories of a plurality of consumers for the product;
Identification information for obtaining identification information of each of a plurality of consumers who have accessed the consumer database and performed consumption behavior on a predetermined product corresponding to the product-related identification information specified by the first operation signal Acquisition means;
A clustering database storing clustering information in which identification information of a plurality of consumers and a plurality of units are associated by clustering executed in advance;
Consumer counting means for accessing the clustering database and counting the number of consumers whose identification information has been acquired by the identification information acquiring means for each unit;
Image generating means for generating image information, displaying at least one identifier corresponding to the number of consumers belonging to the unit counted by the consumer counting means in a unit display area corresponding to each unit And having
The image generating means includes
Lattice image generating means for displaying the plurality of unit display areas in unit lattices of the same size, and generating image information for arranging and displaying the plurality of unit lattices in a hexagonal lattice shape. An information analysis processing system comprising: A second operation input means for inputting a second operation signal for specifying a period range in which the product is consumed, which is an analysis processing target;
The identification information acquisition means includes
Accessing the consumer database and performing a consumption action on a product corresponding to the product-related identification information specified by the first operation signal within a period range specified by the second operation signal; 2. The information analysis processing system according to claim 1, wherein identification information of each of a plurality of consumers is acquired. The identification information acquisition means includes
The consumer database storing the singing history information in which the identification information of the singing song as the product and the singing history as the consumption behavior history with respect to the singing song is accessed, and is specified by the first operation signal. I was singing for a given singing music piece corresponding to the product-related identification information, the information analysis processing system according to claim 1, wherein the acquiring the respective identification information a plurality of consumers. The first signal input means includes
The information analysis processing system according to claim 3, wherein the first operation signal designating singer identification information corresponding to the singing song to be analyzed is input as the product related identification information. A signal input procedure for inputting an operation signal for specifying product-related identification information related to a product to be analyzed;
Corresponding to the product related identification information specified by the operation signal by accessing a consumer database storing consumption history information in which identification information of a plurality of products and consumption behavior histories of a plurality of consumers for the product are associated An identification information acquisition procedure for acquiring identification information of each of a plurality of consumers who have performed consumption behavior on the predetermined product,
Access a clustering database storing clustering information in which identification information of a plurality of consumers and a plurality of units are associated by clustering executed in advance, and the number of consumers whose identification information has been acquired in the identification information acquisition procedure A consumer counting procedure that counts for each unit;
An image generation procedure for generating image information, in which at least one identifier corresponding to the number of the consumers belonging to the unit counted in the consumer counting procedure is displayed in a unit display area corresponding to each unit. And having
The image generating means includes
Lattice image generating means for displaying the plurality of unit display areas in unit lattices of the same size, and generating image information for arranging and displaying the plurality of unit lattices in a hexagonal lattice shape. An information analysis processing method characterized by comprising:

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