JP2013130921A - Information processing device, information processing method, and information processing program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To ensure the number of recommendable items to maintain precision of recommendation while reducing computational effort.SOLUTION: A selected use relevant information creation section performs the steps of: referring to a storage section storing use relevant information in which user identifiers, item identifiers and use period information are associated; and selecting selected use relevant information that is at least part of plural pieces of use relevant information associated with an item identifier, for each item identifier, on a condition that more pieces of selected use relevant information would be selected when the number of pieces of use relevant information including use period information that is close to a specific point in time is larger. An association calculation section calculates a degree of association between one item identifier and an other item identifier on the basis of selected use relevant information on the one item identifier and selected use relevant information on the other item identifier.

Description

  The present invention relates to an information processing apparatus, an information processing method, and an information processing program for calculating a degree of association between items using a use history related to a user's item.

  In recent years, digital contents such as documents, music, images, and videos distributed and provided using a network have been greatly increased due to advances in digital technology and network technology. Along with this, there is an increasing need for services that recommend items such as digital contents that meet user preferences. As a technique for meeting such needs, a technique for providing a recommended item using a user's browsing history, evaluation history, usage history such as a purchase history, etc., has been developed.

For example, there is a recommendation process using collaborative filtering as one of the techniques for recommending items. In recommendation processing using collaborative filtering, a large number of usage histories are accumulated, and items that match the user's preference are recommended using the usage histories. Also, an item highly relevant to the item that the user is interested in is recommended.
In addition, technology for shortening the processing time required for item recommendation has been developed.
For example, Patent Literature 1 and Patent Literature 2 disclose devices that shorten the processing time by limiting the amount of usage history data used for item recommendation processing.
The apparatus of Patent Literature 1 first calculates an estimated value of the time required for the recommendation process based on the specified minimum number of usage histories and the number of recommended users. Then, the use history is extracted up to the minimum number determined so that the estimated value of the processing time falls within the target time, and the recommendation process is performed using only the extracted use history.

  The device of Patent Document 2 sorts the usage history of recommended users according to conditions such as browsing / purchase count, browsing time, latest date / time of browsing / purchasing, and selects the top Ng1 items (Ng1 is an arbitrary positive number) The recommendation process is performed using only the selected Ng usage history.

JP2006-302097 JP2002-024694

  In the recommendation process of collaborative filtering, there is a problem that the amount of calculation becomes enormous when processing a large amount of usage history data. For this reason, there are cases where a system with high computing power is required, and it is difficult to perform recommendation processing in a practical time. In addition, there is a method of performing recommendation processing in a practical time by using only a part of the usage history without using the entire usage history, but the number of items that can be recommended cannot be secured sufficiently, or the user Since only a part of the user's preference is reflected, the accuracy of the recommendation may be reduced, so that the user's interest and reliability with respect to the recommendation result may be lost.

In the apparatus of Patent Document 1, since the minimum number is extracted from all the usage histories by any method and the recommendation process is performed using the extracted usage histories, the amount of calculation can be reduced. When extracted, the usage history may be biased toward some items, so that the number of items that can be recommended may not be sufficiently secured. In addition, there are cases where items that are frequently used recently are not included in the recommendation result, and the accuracy of recommendation may be lowered.
Also, according to the method of Patent Document 2, by selecting the top Ng1 usage histories in order of the date / time of browsing / purchasing for each user, the recommendation process is performed using the latest usage history while reducing the amount of calculation. Although it can be performed, there is a problem that it is difficult to set Ng1 appropriately. That is, if Ng1 is increased, a large amount of usage history is extracted, so that the effect of reducing the amount of calculation can hardly be obtained. In addition, when Ng1 is made small, a user with a small usage history has relatively little influence, but a user with a large number of usage histories uses only a part of the usage history for recommendation processing, so the recommendation accuracy is low. Sometimes it became. In this way, it is difficult to set an appropriate Ng1 in a situation where there are various users with different numbers of usage and usage forms. For this reason, the effect of reducing the amount of calculation can hardly be obtained, and the recommendation accuracy may be lowered. Further, as a method different from the method of Patent Document 2, a method of selecting a predetermined number of usage histories in order of the date and time of browsing / purchasing for each item can be considered, but even if such a method is used, Since it is difficult to set the predetermined number appropriately, there is a case where the effect of reducing the amount of calculation is hardly obtained or the accuracy of recommendation is lowered.

  Therefore, an object of the present invention is to reduce the amount of calculation while ensuring the number of items that can be recommended and maintaining the accuracy of recommendation.

In order to solve the above-described problems of the related art, the present invention provides a user identifier for uniquely identifying a user who uses an item, or a terminal identifier for uniquely identifying a terminal device used by the user to use the item. A storage unit that stores use-related information in which at least one of the use-subject identifier, the item identifier for identifying the item to be used, and the use time information regarding the use time of the item are associated with each other And for each item identifier, a plurality of the usage related information in the item identifier is selected based on a condition that the more usage related information including the usage time information close to a specific time is selected. A selection usage related information creation unit for selecting selection usage related information that is at least a part of the information, and the selection usage related information creation The one item identifier based on the selection usage related information in the one item identifier selected by and the selection usage related information in the item identifier other than the one item identifier selected by the selection usage related information selection unit And an association degree calculation unit for calculating an association degree between the item identifier and the other item identifier.
In addition, in order to solve the above-described problems of the related art, the present invention relates to a user identifier for uniquely identifying a user who uses an item, or a terminal used by the user to use the item. A user entity identifier that is at least one of terminal identifiers for uniquely identifying a device, an item identifier for identifying an item to be used, and use time information regarding the use time of the item are associated with each other For each item identifier based on a condition such that the more usage related information including the usage time information close to a specific time point is selected, the storage unit storing the used usage related information is referred to. Selection usage related information selection for selecting selection usage related information that is at least a part of the plurality of usage related information in the item identifier And other items other than the one item identifier selected by the selected usage related information selection step and the selected usage related information selected by the selected usage related information selection step. There is provided an information processing method comprising a relevance level calculating step of calculating a relevance level between the one item identifier and the other item identifier on the basis of selection usage related information in the identifier.
In addition, in order to solve the above-described problems of the conventional technology, the present invention uniquely identifies a user identifier for uniquely identifying a user who uses an item or a terminal device used by the user to use the item. Usage-related information in which at least one of the terminal identifiers to be used, the item identifier for identifying the item to be used, and the usage date information regarding the usage date of the item are associated with each other And for each item identifier, a plurality of items in the item identifier are selected based on a condition such that the more usage-related information including the usage time information close to a specific time point is selected. A selection usage related information selection step for selecting selection usage related information that is at least a part of the usage related information. The selected usage related information in the one item identifier selected in the selected usage related information selection step, and the selected usage related information in the item identifier other than the one item identifier selected in the selected usage related information selection step. An information processing program is provided that executes a relevance level calculating step of calculating a relevance level between the one item identifier and the other item identifier.

  According to the information processing apparatus, the information processing method, and the information processing program of the present invention, it is possible to reduce the amount of calculation while maintaining the accuracy of recommendation.

It is a figure which shows the structure of the whole system in embodiment of this invention. It is a figure which shows the structure of the information processing server apparatus 1 in embodiment of this invention. It is a figure which shows the storage state of the user information storage part 131 in embodiment of this invention. It is a figure which shows the storage state of the item information storage part 132 in embodiment of this invention. It is a figure which shows the storage state of the utilization log | history storage part 133 in embodiment of this invention. It is a figure which shows the storage state of the selection condition storage part 134 in embodiment of this invention. It is a figure which shows the image of the period applicable to the selection conditions in embodiment of this invention. It is a figure which shows the storage state of the selection utilization log | history storage part 135 in embodiment of this invention. It is a figure which shows the storage state of the related item information storage part 136 in embodiment of this invention. It is a flowchart which shows the procedure of the selection utilization log | history selection process at the time of using the 1st storage format of selection conditions in embodiment of this invention. It is a figure which shows the example of selection of the 1st condition of step S106 of the selection utilization log | history selection process at the time of using the 1st storage format of the selection conditions in embodiment of this invention. It is a flowchart which shows the procedure of the selection utilization log | history selection process at the time of using the 2nd storage format of selection conditions in embodiment of this invention. It is a figure which shows the example of selection of the selection utilization log | history of step S211 of the selection utilization log | history selection process at the time of using the 2nd storage format of selection conditions in embodiment of this invention. It is a flowchart which shows the procedure of the related item selection process in embodiment of this invention. It is a figure which shows the storage state of the utilization information storage part in embodiment of this invention. It is a figure which shows the example of the purchase history in the music sales site in embodiment of this invention. It is a figure which shows the example of the purchase history in the music sales site in embodiment of this invention.

  The information processing apparatus, information processing method, and information processing program of the present invention will be described below with reference to the accompanying drawings. The item in the present invention may be digital content such as text, voice, music, video, web page, and various articles, or may be information on financial products, real estate, and people. It may also be clothing or food. That is, the item in the present invention may be tangible or intangible, whether it is paid or free.

Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. FIG. 1 is a configuration diagram of the entire system according to an embodiment of the present invention. In the system according to the present embodiment, the information processing server device 1 and one or more terminal devices 3 (3a to 3n) are connected via a network 2.
The network 2 is a network such as the Internet, for example, and mediates exchange of information between the information processing server device 1 and the terminal device 3.

The terminal device 3 is a general computer equipped with a CPU, RAM, ROM, hard disk drive, network interface, or the like, or a portable information terminal such as a mobile phone, a smartphone, or a tablet PC. Send and receive related item details. Note that the usage history and usage information to be described later are collectively referred to as usage-related information.
The usage history is information related to the use of items by the user, and includes at least an item identifier that uniquely identifies an item that has been used. The usage history is a user identifier that uniquely identifies a user (user) who is using the terminal device 3 or a terminal identifier that uniquely identifies the terminal device 3 that the user has used to use the item. At least one of them and usage time information are included. In the present embodiment, a case where a user identifier is used will be described as an example, but the same applies to a case where a terminal identifier is used. The usage history may include information such as an evaluation (evaluation value) on the item of the user and an amount (payment amount) paid for the item. The related item detailed information is information related to an item (related item) related to an item (reference item) browsed or purchased by the user, and transmits information including at least the item identifier of the reference item to the information processing server device 1. It is information that can be obtained by doing.

The information processing server device 1 is a general computer including a CPU, a RAM, a ROM, a hard disk drive, a network interface, and the like that provide related item information to the terminal device 3 according to a usage history. Further, it is also possible to implement as software (program) processing using a computer including a CPU, RAM, ROM, hard disk drive (HDD), network interface, and the like.
FIG. 2 is a configuration diagram of the information processing server apparatus 1 in the present embodiment. The information processing server device 1 in this embodiment includes an information processing server control unit 11, an information processing server communication unit 12, and an information processing server storage unit 13 that is a storage unit that stores various types of information. The

  The information processing server communication unit 12 has a function for communicating with the terminal device 3 via the network 2.

The information processing server storage unit 13 stores various data using a storage device such as an HDD. The information processing server storage unit 13 includes a user information storage unit 131, an item information storage unit 132, a usage history storage unit 133, a selection condition storage unit 134, a selection usage history storage unit 135, and a related item information storage unit 136. And is configured.
The user information storage unit 131 stores a plurality of user information. FIG. 3 is a diagram illustrating a storage state of the user information storage unit 131. The user information is obtained by associating the user identifier (user_id) with the user attribute information (user_info), and is stored in a table format as shown in FIG. The user attribute information is information such as the user's name, age, gender, address (region), hobby, membership time (year, month, date, date, etc.), e-mail address, telephone number, and the like.

  The item information storage unit 132 stores a plurality of item information. FIG. 4 is a diagram illustrating a storage state of the item information storage unit 132. The item information is an item identifier (item_id) and item attribute information (item_info) associated with each other, and is stored in a table format as shown in FIG. The item attribute information is, for example, information such as an item name, a creator, a production year, a genre, a price, and a user condition suitable for using the item.

  The usage history storage unit 133 stores a plurality of usage histories received from the terminal device 3. FIG. 5 is a diagram illustrating a storage state of the usage history storage unit 133. The usage history is an association of an item identifier (item_id), a user identifier (user_id), and usage time information (dl_date), and is stored in a table format as shown in FIG. It is assumed that the usage history received from the terminal device 3 includes usage time information. However, if the usage history information is not included, the date and time when the usage history is stored is set. What is necessary is just to memorize | store as utilization time information. If the usage history includes information other than the above, the usage history may be stored in the usage history storage unit 133 including the information.

  The selection condition storage unit 134 stores a plurality of selection conditions. The selection condition indicates a condition for selecting a selection usage history (selection usage related information) from a plurality of usage histories. By using this selection condition, an item with a larger number of recently used users can be selected with a larger selection usage history. The selection usage history is a usage history used for related item selection processing described later. FIG. 6 (FIGS. 6A to 6B) is a diagram showing the storage state of the selection condition storage unit 134. FIG. 7 (FIGS. 7A to 7B) is a diagram showing an image of a period corresponding to the selection condition. Hereinafter, two types of storage formats of selection conditions will be described with reference to FIGS. 6 and 7.

  The first storage format of the selection conditions is an association between the acquisition period (period) and the acquisition limit number (limit_log) (first condition), and a plurality of storage conditions are stored in a table format as shown in FIG. To do. The first condition is that the acquisition limit number decreases as the acquisition period becomes longer. A case where there are three first conditions (acquisition period, acquisition limit number), c1 (30 days, 20), c2 (90 days, 10), and c3 (150 days, 5) will be described. The acquisition period in the first condition indicates the length of a period from a past point in time (acquisition start time) to a predetermined point in time (acquisition end time). As shown in FIG. The acquisition end times of the acquisition periods of the conditions are the same. In addition, the acquisition start time of the acquisition period of the first condition is different for each first condition because it is a time that goes back in the past by the number of days of the acquisition period from the acquisition end time. The selection usage history is selected for each item according to the acquisition limit number from the usage history regarding the user who used the item between the acquisition start time and the acquisition end time corresponding to the acquisition period of the first condition. The

Note that the first condition may be set so that all the latest usage histories can be acquired. Specifically, for the one with the shortest acquisition period among the first conditions, for example, a special acquisition limit number such as symbols “∞” and “0” representing infinity is set. Then, when selecting the selection usage history, if a special acquisition limit number is set in the first condition, all the usage history within the acquisition period may be selected as the selection usage history. In addition, a first condition may be set such that at least one usage history corresponding to an item that has been used once can be acquired. Specifically, the acquisition period may be set so that the acquisition start time of the acquisition period of the first condition having the smallest acquisition limit among the first conditions matches the service start time.

  The second storage format of the selection conditions is an association of the application order (order), which is the order of the selection conditions to be applied, the difference acquisition period (dif_period), and the acquisition limit number (limit_log) (second condition). A plurality of data are stored in a table format as shown in FIG. In the second condition, the acquisition limit number decreases according to the application order. When there are three second conditions (application order, difference acquisition period, acquisition limit number), c1 (1, 30 days, 20), c2 (2, 60 days, 10), and c3 (3, 60 days, 5) As shown in FIG. 7B, the difference acquisition periods of the second condition do not overlap each other. Further, when the application order is continuous, such as c1 and c2, the acquisition end time of the second condition whose application order is earlier matches the acquisition start time of the second condition whose application order is later. The selected usage history is selected for each item according to the acquisition limit number from the usage history related to the user who used the item between the acquisition start time and the acquisition end time corresponding to the difference acquisition period of the second condition. Is done.

Note that the second condition may be set so that all the latest usage histories can be acquired. Specifically, a special acquisition limit number such as symbols “∞” and “0” representing infinity is set for the second condition having the application order of “1”. Then, when selecting the selection usage history, if a special acquisition limit number is set in the second condition, all the usage history within the acquisition period may be selected as the selection usage history. In addition, a second condition may be set such that at least one usage history corresponding to an item that has been used once can be acquired. Specifically, the difference acquisition period may be set so that the acquisition start time of the difference acquisition period of the second condition having the latest application order among the second conditions matches the service start time.

In FIG. 6, the acquisition period and the difference acquisition period are expressed in days, but may be in time units or in seconds. Further, instead of the number of days, a combination of the acquisition start time and the acquisition end time of the period may be stored. In addition, in the second storage format of the selection condition, since the descending order of the acquisition limit number matches the application order, if the descending order of the acquisition limit number is used instead of the ascending order of the application order in the subsequent processing, the application order is changed. Can be omitted. The method of using the selection conditions in the acquisition order will be described in detail in the process of the selection usage history creation unit 112.
In addition to the above two selection conditions, the usage history at a time close to a specific time that is the acquisition end time of the acquisition period of the first condition or the acquisition time of the acquisition period of the second condition in the application order “1” As long as an item has a larger number of usage histories, the condition may be used as the selection condition.

  The selection usage history storage unit 135 stores a plurality of selection usage histories. FIG. 8 is a diagram illustrating a storage state of the selection usage history. As with the usage history, the selection usage history is an item identifier (item_id), user identifier (user_id), and usage time information (dl_date) associated with each other, and is stored in a table format as shown in FIG. In the case where other information is included in the selected usage history, other information may be stored in the selected usage history storage unit 135.

  The related item information storage unit 136 stores a plurality of related item information. FIG. 9 is a diagram illustrating a storage state of related item information.

The related item information is obtained by associating the item identifier (base_item_id) of the reference item, the item identifier (rel_item_id) of the related item, and the degree of association (r_value), and is stored in a table format as shown in FIG. Although base_item_id and rel_item_id are both item_id, different names are used to distinguish them.

  The information processing server control unit 11 performs overall control on each unit configuring the information processing server device 1. The information processing server control unit 11 includes a usage history registration unit 111, a selection usage history creation unit 112, a related item selection unit 113, a related item provision unit 114, and a relevance degree calculation unit 115. . The selection usage history creation unit 112 and a selection usage information creation unit described later are collectively referred to as a selection usage related information creation unit.

When the usage history is received from the terminal device 3, the usage history registration unit 111 stores the received usage history in the usage history storage unit 133.
The selection usage history creation unit 112 performs a selection usage history selection process at every predetermined timing. As the predetermined timing, a predetermined time interval (for example, every 24 hours) may be used, or a usage history may be received a certain number of times. Also, the time interval may vary from Monday to Friday every 3 hours, Saturday every 6 hours, and Sunday every 12 hours. Also, the time interval may be changed according to the season, such as shortening the time interval in summer and increasing the time interval in winter. The selection use history selection process differs depending on the storage format of the selection conditions.

First, the selection use history selection process when the first condition is used will be described with reference to the flowchart of FIG.
First, the selection usage history creation unit 112 deletes all the selection usage histories stored in the previous selection usage history selection process in the selection usage history storage unit 135 (step S101).
Next, the selection usage history creation unit 112 acquires all the first conditions from the selection condition storage unit 134 (step S102).

Next, the selection usage history creation unit 112 sets an acquisition start time and an acquisition end time for each first condition acquired in step S102 (step S103). The acquisition end time is determined by an acquisition end time setting rule predetermined by the service provider. Note that, in any first condition, the acquisition end time is the same time. For example, the acquisition end time setting rule may set the time at which the selection use history selection process is performed as it is as the acquisition end time, or the use history up to the day before the selection use history selection process is selected. May be set as the acquisition end time. The acquisition start time is set so that the period from the acquisition start time to the acquisition end time matches the acquisition period of the first condition. The use history having the use time information corresponding to the period from the acquisition start time to the acquisition end time is set as the specific use history.
Next, the selection usage history creation unit 112 selects the first condition (longest period condition) that maximizes the acquisition period from the first conditions acquired in step S102, and from the usage history storage unit 133, All item_ids included in the specific usage history corresponding to the longest period condition are extracted without duplication (step S104).

Next, the selection usage history creation unit 112 selects one item_id extracted in step S104, for example, in the order of extraction (step S105).
Next, the first use history creation unit 112 sets a first condition that maximizes the number of obtainable specific use histories including the item_id selected in step S105 from the first condition obtained in step S102. One is selected (step S106). The number that can be acquired is the lower of the number of specific usage histories including item_id selected in step S105 and the acquisition limit number corresponding to the first condition. When there are a plurality of first conditions that maximize the number of obtainable items, the first condition that has the shortest acquisition period may be selected from among the first conditions that maximize the number of obtainable items.

Next, the selection usage history creation unit 112 extracts from the usage history storage unit 133 all of the specific usage history corresponding to the first condition selected in step S106, including the item_id selected in step S105. (Step S107). The specific usage history extracted here is used as the selection candidate usage history.
Next, the selection usage history creation unit 112 selects as the selection usage history from the selection candidate usage history extracted in step S107 up to the acquisition limit number of the first condition selected in step S106 (step S108). At this time, for example, selection may be made in order from the newest use time information.
Next, the selection usage history creation unit 112 registers the selection usage history selected in step S108 in the selection usage history storage unit 135 (step S109).

  Next, the selection usage history creation unit 112 determines whether or not all the item_id extracted in step S104 have been selected in step S105 (step S110). If all are selected, the series of processing from step S101 to step S110 is terminated, and if unselected items still remain, the process proceeds to step S105.

  Here, in the selection use history selection process when the first condition is used, as the first condition (acquisition order, acquisition period), c1 (30 days, 20), c2 (90 days, 10), An example of the selection of the first condition in step S106 for two items (item A, item B) when there are three c3 (150 days, five) will be described with reference to FIG.

First, the selection usage history creation unit 112 refers to the usage time information in the item identifier to be selected, and counts the number of usage related information included in each acquisition period with the acquisition limit number as an upper limit. That is, the above-mentioned acquirable number is counted. As shown in FIG. 11A, the number of specific usage histories of the item A corresponding to the acquisition period 30th of the first condition c1 is “6”, and the item corresponding to the acquisition period 90th of the first condition c2. When the number of specific usage histories of A is “18” and the number of specific usage histories of item A corresponding to the acquisition period 150 days of the first condition c3 is “32”, in each first condition, The number of specific usage histories that can be acquired for item A is “6”, “10”, and “5”, respectively.
Then, the selection usage history creation unit 112 selects the usage related information included in the acquisition period in which the counted number of usage related information (acquisable number) is the largest as the selection usage related information in the item identifier to be selected. In item A, the first condition c2 that maximizes the number of items that can be acquired is selected, and the first condition c18 is obtained from the specific usage history “18” items corresponding to the acquisition period 90 days of the first condition c2. The c2 acquisition limit number “10” is set as the upper limit, and it is selected as selection-use related information.

Further, as shown in FIG. 11B, the number of specific usage histories of item B corresponding to the acquisition period 30th of the first condition c1 is “13”, corresponding to the acquisition period 90th of the first condition c2. When the number of specific usage histories of item B to be “17” and the number of specific usage histories of item B corresponding to the acquisition period 150 days of the first condition c3 is “25”, each first condition , The number of specific usage histories that can be acquired for item B is “13”, “10”, and “5”, respectively. For this reason, for item B, the first condition c1 that maximizes the number of obtainable items may be selected. Thus, the number of specific usage histories in the acquisition period of 150 days is larger for item A than for item B, but since item B is more recently used by many users, the selected usage history is The number of items B is larger for item B.
The above is the description of the selection use history selection process when the first condition is used. In this way, by referring to the usage time information in the user subject identifier to be selected, the number of usage related information included in each acquisition period is counted up to the limit of acquisition, and the number of usage related information counted (acquisable The usage related information included in the acquisition period with the largest number) is selected as the selected usage related information in the selection subject identifier.

Next, the selection use history selection process when the second condition is used will be described with reference to the flowchart of FIG.
First, the selection usage history creation unit 112 deletes all the selection usage histories stored in the previous selection usage history selection process in the selection usage history storage unit 135 (step S201).
Next, the selection usage history creation unit 112 acquires all the second conditions from the selection condition storage unit 134 (step S202).
Next, the selection and use history creation unit 112 initializes the acquisition end time (step S203). The initial setting of the acquisition end time may be performed according to the acquisition end time initial setting rule predetermined by the service provider. The acquisition end time initial setting rule may be set, for example, as the acquisition end time as it is as the time at which the selection use history selection process is performed, or the use history up to the day before the selection use history selection process is selected. As such, it may be set as the acquisition end time.

Next, the selection usage history creation unit 112 selects one second condition acquired in step S202 in ascending order of application order (step S204).
Next, the selection usage history creation unit 112 sets an acquisition start time according to the second condition selected in step S204 (step S205). The acquisition start time is set so that the period from the acquisition start time to the acquisition end time matches the difference acquisition period of the second condition. The use history having the use time information corresponding to the period from the acquisition start time to the acquisition end time is set as the specific use history.
Next, the selected usage history creation unit 112 extracts all item_ids included in the specific usage history corresponding to the second condition selected in step S204 from the usage history storage unit 133 without duplication (step S206).
Next, the selection usage history creation unit 112 selects one item_id extracted in step S206, for example, in the order of extraction (step S207).

Next, the selection usage history creation unit 112 calculates the number of registrations of the selection usage history corresponding to the item_id selected in step S207 (step S208). In order to calculate the number of registrations, the selection usage history stored in the selection usage history storage unit 135 may be counted including the item_id selected in step S207.
Next, the selection usage history creation unit 112 determines whether or not the acquisition limit number of the second condition selected in step S204 is larger than the registration number calculated in step S208 (step S209). If it is larger than the registered number, the process proceeds to step S210. If it is equal to or smaller than the registered number, the process proceeds to step S213.
In step S210, the selected usage history creation unit 112 receives all items including the item_id selected in step S207 from the usage history storage unit 133 among the specific usage history corresponding to the second condition selected in step S204. Extract. The specific usage history extracted here is used as the selection candidate usage history.

Next, the selection usage history creation unit 112 subtracts the registration number calculated in step S208 from the acquisition limit number of the second condition selected in step S204 from the selection candidate usage history extracted in step S210. Up to the possible number is selected as selection usage history (step S211). At this time, for example, selection may be made in order from the newest use time information.
Next, the selection usage history creation unit 112 registers the selection usage history selected in step S211 in the selection usage history storage unit 135 (step S212). Next, it progresses to step S213.
In step S213, the selection usage history creation unit 112 determines whether or not all item_id extracted in step S206 have been selected in step S207. If all are selected, the process proceeds to step S214, and if there are still unselected ones, the process proceeds to step S207.

In step S214, the selection usage history creation unit 112 determines whether or not all the second conditions acquired in step S202 have been selected in step S204. If all are selected, the series of processing from step S201 to step S215 is terminated, and if unselected items still remain, the process proceeds to step S215.
In step S215, the selection usage history creation unit 112 updates the acquisition end time so as to coincide with the acquisition start time set in step S205. Next, the process proceeds to step S204.

  Since the acquisition limit number of the second condition is reduced according to the application order, the item whose registration number exceeds the acquisition limit number at an early stage of the application order (that is, an item having a large number of recently used users) is larger. Can be selected as the selected usage history.

  Here, in the selection usage history selection process when the second condition is used, c1 (1, 30 days, 20), c2 (as the second condition (application order, difference acquisition period, acquisition limit number)) FIG. 13 shows an example of selection of the selection usage history in step S211 for two items (item A, item B) when there are three items, ie, 2, 60 days, 10 items) and c3 (3, 60 days, 5 items). Will be described. In item A, as shown in FIG. 13A, the acquisition limit number of the second condition c1 in the application order “1” is “20” and the registration number is “0”, so the difference acquisition period All “6” specific usage histories of item A corresponding to the 30th day are selected as selection usage histories.

Next, the process proceeds to the second condition c2 in the application order “2”, and the acquisition limit number of the condition c2 is “10”, and the total number of selected use histories selected as the registration number is “6”. From the “12” specific usage histories of the item A corresponding to the difference acquisition period 60, “4” items are selected as the selection usage history in the order of the new usage time information.
Since the acquisition limit number of the second condition c3 in the application order “3” is “5” and the total number of selected usage histories selected as the number of registrations is “10”, the selection usage history is selected. Do not do.

In item B, as shown in FIG. 13B, the number of acquisition limits for the second condition c1 in the application order “1” is “20” and the number of registrations is “0”. All “13” specific usage histories of item B corresponding to the acquisition period 30 days are selected as selection usage histories. Next, the selected usage history is selected with the acquisition limit number of the second condition c2 in the application order “2” being “10” and the total number of the selected selection usage histories being the registration number being “13”. Absent. Since the acquisition limit number of the second condition c3 in the application order “3” is “5” and the total number of selected usage histories selected as the number of registrations is “13”, the selection usage history is again here. Do not elect. Thus, the total number of specific usage histories in the total difference acquisition period is larger for item A, such as “32” for item A and “25” for item B, but item B is more recent. Since many items are used, item B has a larger number of usage histories to be selected.

The above is the description of the selection use history selection process when the second condition is used. In this way, in order from the selection condition corresponding to the difference acquisition period close to a specific point in time, the usage-related information is selected for each item identifier with the acquisition limit number in the selection condition as the upper limit, and is currently used for selection. If the acquisition limit in the selection condition is greater than the number of registrations, which is the total number of selection-use related information that has already been selected in the item identifier to be selected, the registration number is subtracted from the acquisition limit in the selection conditions currently used for selection. By selecting the usage related information up to the upper limit, the selection usage related information in the item identifier is selected.
Even when the first condition is used and when the second condition is used, there are multiple uses of the same user for the same item, that is, multiple usage histories with the same combination of (item_id, user_id). If it exists, in each step of the selection use history selection process, it is possible to use only the latest use time information among the use histories having the same (item_id, user_id) and not use the others. Good. By using only the latest usage history, the number of users used for the recommendation process can be sufficiently secured.
As described above, by performing the selection use history selection process using the first condition or the second condition, it has been used frequently recently, that is, the opportunity of browsing related items by many users most recently. Many usage histories of reference items are acquired, and the accuracy of recommendation can be maintained. In addition, the number of reference items that have not been used much recently, that is, because there is no opportunity for most users to view related items recently, does not greatly affect the accuracy of recommendation. Thus, it is possible to obtain a high calculation amount reduction effect. In addition, since the usage history can be extracted although the number is small, related items can be selected even with reference items that have not been used much recently, and the number of recommended reference items can be secured.

The degree-of-relevance calculation unit 115 calculates the degree of association after the selection / use history selection process by the selection / use history creation unit 112 is completed, and then the related item selection unit 113 performs a related item selection process.
The related item selection process will be described with reference to the flowchart of FIG.
First, the related degree calculation unit 115 deletes related item information stored in the related item information storage unit 136 (step S301). There are the following two methods for deleting related item information.
The first method of deleting related item information is a method of deleting all related item information stored in the related item information storage unit 136. Since this method deletes all related item information without performing selection, the amount of processing is reduced.

  The second method of deleting related item information is a method of deleting only related item information of reference items for which new related item information is created in the processing after step S302 from among related item information. In the related item information, only the reference item corresponding to item_id included in the selected usage history stored in the selected usage history storage unit 135 is created. Therefore, it can be realized by deleting only related item information having base_item_id that matches item_id included in any of the selected usage histories stored in the selected usage history storage unit 135.

This method can leave past related item information for a reference item for which new related item information is not newly created in the processing from step S302.

Next, the relevance calculation unit 115 extracts all item_ids without duplication from the selected usage history storage unit 135 (step S302).
Next, the degree-of-association calculation unit 115 selects one item_id as the reference item item_id in the order of extraction among the item_id extracted in step S302 (step S303).
Next, the degree-of-association calculation unit 115 acquires all the selection usage histories including the item_id selected in step S303 from the selection usage history storage unit 135 as reference selection usage histories (step S304).

  Next, the relevance calculation unit 115 selects the item_id selected in step S303 from the selection usage history including the user_id included in any of the reference selection usage history acquired in step S304 from the selection usage history storage unit 135. All item_ids other than are extracted without duplication as item_id of related candidate items (step S305).

Next, the degree-of-relevance calculation unit 115 acquires, as a related candidate selection usage history, a selection usage history including any of the item_ids of the related candidate items extracted in step S305 from the selection usage history storage unit 135 (step S306). .
Next, the degree-of-association calculation unit 115 calculates the degree of association with the reference item for each related candidate item using the reference selection usage history and the related candidate selection usage history (step S307). As a method of calculating the degree of association, for example, a Jaccard coefficient between a set of users included in the reference selection usage history and a set of users included in the related candidate selection usage history corresponding to the related candidate item may be used. . In addition, the preference level indicating the degree of preference of the user with respect to the reference item is calculated using the reference selection usage history, the preference level for the related candidate item is calculated using the related candidate selection usage history, and the preference level is used. A cosine distance between two items may be used as the degree of association. Further, the user's preference for the item existing in both the user set included in the reference selection usage history and the user set included in the related candidate selection usage history is regarded as an evaluation given to the item by the user. A product moment correlation coefficient may be used. In addition to the above-described relevance calculation method, various known relevance calculation methods can be used.

As the preference level, values such as the number of use, evaluation value, and payment amount can be used as the preference level, or a value calculated using the sum or product of a plurality of values may be used. Moreover, you may calculate a preference degree using utilization time information.

Further, when calculating the degree of association, weighting can be performed according to the first condition and the second condition which are selection conditions.
First, the relevance weighting according to the first condition will be described.
In order to weight the degree of relevance according to the first condition, the first condition selected for each item is stored in the information processing server storage unit 13 in the selection use history selection process using the first condition. First, a weighting coefficient is calculated such that the smaller the difference in the acquisition period of the selected first condition between the two items is, the larger the coefficient is. The weighting coefficient w (x, y) of two items (item x and item y) is selected for the item y, for example, with the acquisition period of the first condition selected for the item x as p (x) When the obtained acquisition period of the first condition is p (y), it can be calculated by Expression (1) using a constant k (> 0).

Moreover, it is computable by Formula (2) using constant (alpha) (> 0), (beta) 1 (> 0), (beta) 2 (> 0).

Specifically, for example, the first condition selected for the item x is c2 (90day, 10) in FIG. 7A, and the first condition selected for the item y is FIG. In the case of c1 (30 day, 20) of a), “90” is substituted for p (x), and “30” is substituted for p (y), thereby calculating the weighting coefficient w (x, y). can do. Of course, the weighting coefficient may be calculated using other methods. Then, the relevance level v (x, y) is calculated using the simple relevance level v ′ (x, y) and the weighting coefficient w (x, y) calculated using the Jaccard coefficient or the like, And can be calculated by equation (4).

Next, the relevance weighting according to the second condition will be described.
In order to weight the relevance level according to the second condition, the information processing server storage unit stores the second condition in which the selection usage history is selected last for each item in the selection usage history selection processing using the second condition. First, a weighting coefficient is calculated so as to increase as the application order of the second condition selected at the end of the two items is closer. The weighting coefficient w (x, y) of two items (item x and item y) is, for example, that the application order of item x is r (x), the application order of item y is r (y), and formula (1) And p (x) and p (y) in equation (2) can be calculated by replacing them with r (x) and r (y), respectively. The last selected second condition is the second condition when the acquisition limit number is reached.

Specifically, for example, the second condition selected for the item x is c1 (1, 30day, 20) in FIG. 7B, and the second condition selected for the item y is illustrated in FIG. In the case of c3 (3, 60 days, 5) of 7 (b), by assigning “1” to r (x) and “3” to r (y), the weighting coefficient w (x, y) can be calculated. Of course, the weighting coefficient may be calculated using other methods. As in the case of the first condition, the relevance level v (x, y) is calculated by using the simple relevance level v ′ (x, y) using the Jaccard coefficient or the like, and the weighting coefficient w (x, y). Can be calculated by the equation (3) or the equation (4).

  As described above, by considering the selection condition for the degree of relevance, the degree of relevance between two items that were popular at the same time can be increased. This leads to supplementing the accuracy of related items relative to reference items that have not been used much recently. Although related items corresponding to reference items that have not been used much recently are not often viewed, they are not necessarily viewed at all. Therefore, by making it easy to present items that were popular at the same time as related items, when the user browsed the related items, the user felt that “this item was also popular at the same time”, and the recommendation result Can improve the reliability. Note that the weighting coefficient for the first condition or the second condition may be used as it is as the degree of relevance.

Next, the related item selection unit 113 selects related items from the related candidate items based on the degree of relevance calculated in step S307 (step S308). In order to select related items, up to a predetermined number of related candidate items predetermined by the service provider in order from the highest degree of relevance may be selected as related items. Moreover, you may select the related candidate item which has a higher degree of relevance than the predetermined value which the service provision side determined beforehand as a related item. Of course, all the related candidate items may be selected as related items.
Next, the related item selection unit 113 selects, in the related item information storage unit 136, the item_id (base_item_id) of the reference item selected in step S303 and the item selected in step S308 for each related item selected in step S308. The related item information that associates the item_id (rel_item_id) of the related item with the relevance (r_value) calculated in step S307 is stored (step S309).

  Next, the related item selection unit 113 determines whether all the item_id extracted in step S302 have been selected in step S303 (step S310). If all are selected, the series of processing from step S301 to step S310 is terminated, and if there are still unselected ones, the process proceeds to step S303.

As described above, it is possible to select related items with a small amount of calculation by calculating the degree of association using only the selected usage history that is a part of the usage history and selecting related items.
In the related item selection process described above, processing is performed using the selection usage history in both the process related to the reference item (steps S302 and S304) and the process related to the related candidate item (steps S305 and S306). However, if the selected usage history is used in at least one process, the amount of calculation can be reduced even if the usage history is used in the other process.

Further, the selection usage history used for the related item selection processing is extracted such that the larger the usage history at the time close to the processing time (specific time), the larger the item. For this reason, at least in the process related to the related candidate item, if the relevance to the reference item is similar by using the selection usage history, the item that has been used more frequently than the item that has not been used much recently. Is more likely to be recommended as a related item. Also, even if an item has not been used frequently recently, only the number of usage histories is limited, so if it is highly related to the reference item, it is frequently used recently, but it is used with the reference item. It is easier to recommend items as related items than items with a small number of users. In other words, by using the selected usage history, both items that have a high degree of relevance to the reference item and that have been recently used and items that have not been popular recently but that are highly relevant to the reference item are mixed. Since the related items can be presented in the state of being in a state of being in a state, there is an effect that confidence in recommendation is increased and accuracy is increased.
In addition, even if the selected usage history is used only for the processing related to the reference item, the reference item that has been used by many users most recently is selected as the selected usage history. When selecting, sufficient accuracy can be secured. In addition, since the reference item that has not been used most recently, there is almost no opportunity for the related item to be presented, the influence on the accuracy of recommendation is small. Further, since the related items can be selected in order to secure the number of usage histories, although it is a small number, the number of recommended reference items can be secured.

  The related item providing unit 114 transmits the related item detailed information to the terminal device 3 in response to a request from the terminal device 3. Specifically, first, related item information having a base_item_id that matches the item identifier of the reference item received from the requesting terminal device 3 is extracted from the related item information storage unit 136. Next, item information corresponding to an item identifier that matches rel_item_id included in the extracted related item information is acquired from the item information storage unit 132. Then, related item detailed information is created based on the acquired item information, and the created related item detailed information is transmitted to the terminal device 3.

  If there are multiple uses of the same item by the same user, that is, if there are multiple usage histories with the same combination of (item_id, user_id), the usage information created using the usage history is used. The above-described series of processing may be performed. At this time, the usage history received from the terminal device 3 is used only for updating the usage information and is not used in other processes, so that it is not necessary to store the usage history. For this reason, a usage information update unit is prepared instead of the usage history registration unit 111, and a usage information storage unit that stores usage information instead of the usage history storage unit 133 is prepared. In addition, since the usage information is to be selected, a selection usage information creation unit is prepared instead of the selection usage history creation unit 112, and a selection usage information storage unit is prepared instead of the selection usage history storage unit 135. Note that the usage history and usage information are collectively referred to as usage-related information. Further, as described above, the selection usage history creation unit 112 and a selection usage information creation unit described later are collectively referred to as a selection usage related information creation unit.

  FIG. 15 is a diagram illustrating a storage state of the usage information storage unit. The usage information includes an item identifier (item_id), a user identifier (user_id), a usage count (cnt_dl), start usage time information indicating the first usage time (first_dl_date), and a final usage time indicating the last usage time. This is a combination of usage time information (last_dl_date) and is stored in a plurality in the table format of FIG. The combination of (item_id, user_id) is unique and cannot be registered redundantly.

  The usage information update unit updates the usage information every time a usage history is received from the terminal device 3. At this time, if the usage information storage unit does not include usage information that matches the combination of (item_id, user_id) in the received usage history, the combination of the received usage history (item_id, user_id) and the number of usages The usage information is created by associating “1”, the usage time information included in the usage history information as the start usage time information, and the usage time information included in the usage history as the final usage time information. The usage information may be stored in the usage information storage unit. When the usage information storage unit includes usage information that matches the combination of (item_id, user_id) in the received usage history, “1” is added to the usage count of the matched usage information, and the final usage The time information may be updated with the use time information of the received use history. Here, when the evaluation value is included in the usage history, a representative value of the evaluation value (for example, the latest evaluation value) may be associated with the usage information. Further, when the payment amount is included in the usage history, a representative value (for example, a total value or a maximum value) of the payment amount may be associated with the usage information. In addition, representative values (maximum value, minimum value, mode value, median value, latest value, total value, average value, etc.) for values included in the usage history may be associated with the usage information. In other words, the usage information is a result of usage history aggregation.

Since the selection usage information storage unit stores selection usage information (selection usage related information) which is a part of the usage information, the storage format of FIG. 15 is the same as that of the usage information storage unit.
The selection usage information creation unit performs a selection usage information selection process. In both the selection usage information selection process using the first condition and the selection usage information selection process using the second condition, if the final usage time information is used to determine whether it falls within the predetermined period, the selection usage information is used. The selection use history selection process using the first condition and the selection use history selection process using the second condition by the history creating unit 112 can be performed.

In the related item selection processing by the related item selection unit 113 and the related degree calculation unit 115, the same processing can be performed by using the usage information instead of the usage history.
Since the usage information that is the total result of the usage history is stored without storing the usage history, the amount of data stored in the information processing server storage unit 13 can be reduced. Moreover, since the last use time information is updated every time the use history is received, the latest use time information can be obtained immediately.

  Here, the form of the service in which the present invention is highly effective will be described. The present invention is particularly effective for services that have a trend change. FIG. 16 is a diagram in which purchase histories related to the music ID “s98” on the music sales site are arranged in order from the latest purchase time. As shown in FIG. 16, it can be read that the song with the song ID “s98” is popular around April 2011 because the number of purchases in April 2011 is large. FIG. 17 is a diagram in which purchase histories of users related to the music ID “s14” on the music sales site are arranged in order from the latest purchase time. As shown in FIG. 17, a lot of songs with the song ID “s14” are purchased from September 2010 to October 2010, but are rarely purchased around April 2011. Although it was popular around the month, it can be seen that it was not popular around April 2011.

In such a service, when the calculation amount reduction method of the present invention is used, for example, the selection usage history is selected using the first condition of the selection conditions in FIG. In the case of the music ID “s98”, the selection condition c1 (90 days, 20 pieces) is selected, and “17” purchase histories corresponding to the period from April 1, 2011 to April 30, 2011 are selected. Selected as usage history. For the music ID “s14”, the selection condition c3 (150 days, 5) is selected, and “4” purchase histories corresponding to the period from December 2, 2010 to April 30, 2011 are selected and used. Selected as a history. The music ID “s98” that has been popular recently has many influences on recommendation accuracy because the related items are viewed by many users. Therefore, the accuracy of recommendation can be maintained.

In addition, if the relevance with the reference item is the same, that is, if the probability of being used together with the reference item is the same for the same user, the more the selected use history is, Since it becomes easy to be selected as a related candidate item, if the relevance to the reference item is about the same, it corresponds to the music ID “s98” that is more popular than the music corresponding to the previously popular music ID “s14”. Music is more likely to be extracted as a related candidate item for other music. And since related items with a high degree of relevance to the reference item are selected from related candidate items that include many items that have recently been used, items that have a high degree of relevance with the reference item and are currently used are related items. It is easy to be elected as. For this reason, it is possible to select related items with high accuracy while reducing the amount of calculation.

In the above service, in order to reduce the amount of calculation, if a predetermined number of purchase histories are uniformly extracted for all items and related items are selected, if the predetermined number is large, the amount of calculation Reduction effect will fade. On the other hand, when the predetermined number is small, for example, the usage history number of the music ID “s98” that is currently in circulation that has a large effect on the recommendation accuracy cannot be secured sufficiently, and the recommendation accuracy is maintained. It may not be possible.
In addition, when a method for extracting only a purchase history for a predetermined period is used to reduce the calculation amount in the service as described above, if the predetermined period is shortened in order to increase the calculation amount reduction effect, There is a possibility that the number of reference items to be updated cannot be sufficiently secured, the related items for the majority of reference items are not updated, the user loses interest in the recommendation result with little change, and the accuracy cannot be maintained. Conversely, if the predetermined period is lengthened in order to secure a large amount of reference items, the effect of reducing the amount of calculation is diminished.

  As described above, according to the information processing apparatus, the information processing method, and the information processing program of the present invention, the selection usage history is selected so that the usage history related to the most recently used item increases, and the selection usage history is used. Select related items. Thus, since the related item is selected using only the selected usage history that is a part of the usage history, the amount of calculation can be reduced.

In addition, for items that have a large impact on the accuracy of recommendations that are frequently used for related items that are frequently used recently, the recommendation process is performed after securing a sufficient number of selection usage histories. . For this reason, it is possible to select related items while maintaining the accuracy of recommendation. In addition, even for a few items that are not frequently used recently, it is possible to secure a selection and use history even though the number is small. For this reason, it is possible to secure a sufficient number of items that can be recommended.

1. Information processing server device (information processing device)
2 Network 3 Terminal device 11 Information processing server control unit 111 Usage history registration unit 112 Selected usage history creation unit (selected usage related information creation unit)
113 Related item selection unit 114 Related item providing unit 115 Relevance degree calculation unit 12 Information processing server communication unit 13 Information processing server storage unit 131 User information storage unit 132 Item information storage unit 133 Usage history storage unit 134 Selection condition storage unit 135 Selection usage History storage unit 136 Related item information storage unit

Claims (9)

User entity identifier that is at least one of a user identifier for uniquely identifying a user who uses the item or a terminal identifier for uniquely identifying the terminal device used by the user for the item, and a target of use The storage unit that stores the usage related information associated with the item identifier for identifying the item and the usage date information related to the usage date of the item is included, and includes the usage date information close to a specific time point. Selection for selecting, for each item identifier, selected usage related information that is at least a part of the plurality of usage related information in the item identifier, based on a condition that the more usage related information is selected. Usage related information creation department,
Based on selection usage related information in one item identifier selected by the selection usage related information creation unit, and selection usage related information in item identifiers other than the one item identifier selected by the selection usage related information selection unit An information processing apparatus comprising: an association degree calculating unit that calculates an association degree between the one item identifier and the other item identifier. The condition is associated with each of a plurality of acquisition periods indicating a period from a certain point in time before the specific point in time to the specific point in time, and the acquisition period is set to a smaller number as the acquisition period is longer. Is a condition using a plurality of acquisition limit numbers,
The selected usage related information creation unit refers to the usage time information in the item identifier to be selected for selecting the selected usage related information, and sets the usage related information included in each of the acquisition periods up to an acquisition limit. The number is counted, and the usage related information included in the acquisition period with the largest number of the counted usage related information is selected as the selected usage related information in the item identifier to be selected. Information processing device.   The degree-of-association calculating unit is configured to acquire the most frequently used usage-related information in the one item identifier, and to acquire the largest number of the usage-related information in the other item identifiers. The information processing apparatus according to claim 2, wherein the degree of association is calculated based on the information. The condition is associated with each of a plurality of difference acquisition periods, which are a plurality of non-overlapping periods indicating a predetermined period in the past from the specific time point, and a difference acquisition far from the specific time point It consists of multiple selection conditions using the acquisition limit number set to a smaller number as the period is longer,
The selection use related information selection unit refers to the use time information in the item identifier to be selected for selecting the selection use related information, in order from the selection condition corresponding to the difference acquisition period close to the specific time point, The usage-related information is selected with the acquisition limit number in the selection condition as the upper limit, and the acquisition limit number in the selection condition currently used for selection is larger than the total number of selected usage-related information in the selection target item identifier In this case, the selection usage related information in the item identifier is selected by selecting the usage related information up to the number obtained by subtracting the total number from the acquisition limit number in the selection conditions currently used for selection. The information processing apparatus according to claim 1.   The relevance calculation unit calculates the relevance based on the selection condition last used for selection in the one item identifier and the selection condition used last in the other item identifier. 5. The information processing method according to claim 4, wherein calculation is performed. The information processing apparatus according to claim 1, wherein the selection usage related information selection unit selects the selection usage related information in order from the usage related information of new usage time information.   The information processing apparatus according to claim 1, further comprising a related item selection unit that selects related items according to the degree of association. The selection and use related information creation unit is at least one of a user identifier for uniquely identifying a user who uses the item or a terminal identifier for uniquely identifying the terminal device used by the user to use the item. Refer to the storage unit that stores usage-related information that associates the usage-subject identifier, the item identifier for identifying the item to be used, and the usage date information related to the usage date of the item. For each item identifier, at least a part of the plurality of usage related information in the item identifier based on a condition such that the more usage related information including the usage time information close to is selected A selection usage related information selection step for selecting selection usage related information;
Selection degree related information in one item identifier selected by the selection usage related information selection step by the relevance calculation unit, and selection in item identifiers other than the one item identifier selected in the selection usage related information selection step A degree-of-association calculating step of calculating a degree of association between the one item identifier and the other item identifier based on usage-related information. On the computer,
User entity identifier that is at least one of a user identifier for uniquely identifying a user who uses the item or a terminal identifier for uniquely identifying the terminal device used by the user for the item, and a target of use The storage unit that stores the usage related information associated with the item identifier for identifying the item and the usage date information related to the usage date of the item is included, and includes the usage date information close to a specific time point. Selection for selecting, for each item identifier, selected usage related information that is at least a part of the plurality of usage related information in the item identifier, based on a condition that the more usage related information is selected. Usage related information selection step,
Based on selection usage related information in one item identifier selected by the selection usage related information selection step, and selection usage related information in other item identifiers selected by the selection usage related information selection step And a degree-of-association calculating step of calculating a degree of association between the one item identifier and the other item identifier.

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