JP2008077385A - Information processing apparatus, method, program and recording medium - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To enable more users to register more useful information for use in recommending items. <P>SOLUTION: An item introduction system 1 lets client users associate items with one another and securitizes the relationship between the items in a simulated fashion, thus allowing the users to freely trade among them. A server 11 introduces the associated items to the users based on the association between the items thus previously registered or traded by the client users. This invention is applicable to information processing apparatuses. <P>COPYRIGHT: (C)2008,JPO&INPIT

Description

  The present invention relates to an information processing apparatus and method, a program, and a recording medium, and in particular, allows a user to register more useful information to be used for item recommendation, and further, the registered information is more The present invention relates to an information processing apparatus and method, a program, and a recording medium that can be effectively used to recommend more effective items.

  In recent years, communication technology has been developed, and various communication services via networks represented by the Internet have become widespread. In order to enable users to appropriately select (for example, purchase) a large amount of content and products that suit their tastes, recommendations to introduce recommended content and products to users There is a foundation (recommendation) system.

  There is a method of presenting an item similar to a certain item in such a recommendation system for content and products by a computer system. There are two technical solutions for that purpose, one based on metadata and the other based on user behavior.

  As a method based on metadata, for example, there is a method used on the site of Pandora.com (http://www.pandora.com/). In the case of this first method, when the user selects an artist or music as a starting point, the music is reproduced one after another based on the similarity of the musical features (metadata) of the artist or music.

  Further, as a method based on the user's behavior, for example, there is a method used on the site of Last.fm (http://www.last.fm). In the case of this second method, the server accumulates the reproduction history of each user's artist (music), and presents the artists that are frequently played by the same user to the user as being similar.

In addition, there is a third method for predicting evaluation of unviewed content by using evaluation information of other users and recommending content that can obtain a good predicted evaluation value (for example, non-patent literature). 1).
P. Resnick, N. Iacovou, M. Suchak, P. Bergstrom, and J. Riedl. “GroupLens: Open Architecture for Collaborative Filtering of Netnews.” Conference on Computer Supported Cooperative Work, pp. 175-186, 1994.

  However, in the case of the first method, the metadata needs to be accurately and sufficiently given, and there is a possibility that enormous cost may be required for that purpose. Further, since metadata is not assigned based on the viewing behavior of the actual user, there is a risk that the presentation is difficult to understand.

  In the case of the second method and the third method, similar content may not be determined for content that no user participating in the service is viewing.

  The present invention has been made in view of such a situation, and in a recommendation system for introducing content and products, the user is allowed to register more useful information for use in item recommendation. In addition, the registered information can be used more effectively so that more effective item recommendation can be performed.

  An aspect of the present invention is an information processing apparatus that provides a user with a service that introduces a related item related to the item from a predetermined item as a reference, and uses the relationship between the items as a stock, Based on the transaction using the consideration of the stock to be performed, the management means for managing the relationship between the items updated by the transaction, and the relationship managed by the management means An information processing apparatus comprising: a presenting unit that determines the related item from a predetermined item and presents the related item to the user.

  A payout means for distributing a payout according to the amount of the stock to a user who has made an association corresponding to the association when a predetermined condition is satisfied based on the related item presented by the presentation means Can further be provided.

  The information processing apparatus further includes a determination unit that determines a related item based on both the relevance managed by the management unit and the metadata of the item, and the presenting unit is configured to determine the related item determined by the determination unit. Can be presented.

  An aspect of the present invention is also an information processing method of an information processing apparatus that provides a user with a service that introduces a related item related to an item from a predetermined item as a reference, the relationship between the items being a stock And a transaction using the consideration of the stock performed between users, a management step for managing the relationship between the items updated by the transaction, and the relationship managed by the processing of the management step Information processing method, a program, or a recording medium on which the program is recorded, including a presentation step of determining the related item from a predetermined item as a reference and presenting it to the user.

  In the aspect of the present invention, the relationship between items is a stock, the transaction using the consideration of the stock performed by users, and the relationship between items updated by the transaction is managed, and the relationship is Based on the predetermined item as a reference, a related item is determined and presented to the user.

  According to an aspect of the present invention, items can be recommended. In particular, it is possible to register more useful information for use in recommending and recommending the item, and to use the registered information more effectively.

  Embodiments of the present invention will be described below. Correspondences between constituent elements of the present invention and the embodiments described in the specification or the drawings are exemplified as follows. This description is intended to confirm that the embodiments supporting the present invention are described in the specification or the drawings. Therefore, even if there is an embodiment which is described in the specification or the drawings but is not described here as an embodiment corresponding to the constituent elements of the present invention, that is not the case. It does not mean that the form does not correspond to the constituent requirements. Conversely, even if an embodiment is described here as corresponding to a configuration requirement, that means that the embodiment does not correspond to a configuration requirement other than the configuration requirement. It's not something to do.

  An aspect of the present invention is an information processing apparatus that provides a user with a service that introduces a related item related to the item from a predetermined item as a reference, and uses the relationship between the items as a stock, Management means (for example, the predicted market processing unit 201 in FIG. 4) that manages the relationship between the items that is performed using the consideration of the stock and that is updated by the transaction, and is managed by the management means An information processing apparatus comprising: a presentation unit (for example, the related item presentation processing unit 202 in FIG. 4) that determines the related item from a predetermined reference item based on the relevance and presents it to the user is there.

  A payout means for distributing a payout according to the amount of the stock to a user who has made an association corresponding to the association when a predetermined condition is satisfied based on the related item presented by the presentation means (For example, the payout processing unit 203 in FIG. 4) may be further provided.

  The presentation unit further includes a determination unit (for example, the item similarity calculation unit 213 in FIG. 4) that determines a related item based on both the relevance managed by the management unit and the metadata of the item. Can present the related item determined by the determining means.

  An aspect of the present invention is also an information processing method of an information processing apparatus that provides a user with a service that introduces a related item related to an item from a predetermined item as a reference, the relationship between the items being a stock And a management step (for example, buy order processing in FIG. 6 and selling in FIG. 8) that manages the relationship between the items, which is updated by the transaction, and the transaction using the price of the stock performed by the users. Order processing), and a presentation step (for example, the presentation process of FIG. 10) that determines the related item from predetermined items based on the relevance managed by the processing of the management step and presents it to the user An information processing method, a program, or a recording medium on which the program is recorded.

  Embodiments of the present invention will be described below.

  FIG. 1 is a block diagram showing a configuration example of an item introduction system to which the present invention is applied.

  In FIG. 1, an item introduction system 1 is composed of a server 11, a client 12, and a client 13 connected via a network 10, and the server 11 introduces (recommends) an item to the client. is there. The item introduction system 1 is used, for example, for a content sales service.

  For example, a client (a user) who desires to purchase content requests content information from the server 11 on the content sales side in order to select the content to be purchased. Based on the request, the server 11 introduces the content information as an item to the requesting client. The user of the client determines whether or not to purchase the content by referring to the introduced content information.

  At this time, the server 11 introduces related items to the user based on the association between items registered in advance by the user of the client. This association indicates a connection from one item to another item, and a parameter indicating the degree (total number or ratio) of the connection is referred to as a degree of association. The association between the items is performed by the market transaction behavior described below by the user of the client.

  As described above, the item introduction system 1 is a recommendation system that introduces items, and is a system that realizes a more desirable item recommendation not only by a user's explicit evaluation behavior but also by inputting a relationship between items. The item introduction system 1 is an approach that is not restricted by the content domain (movies, music, Web pages, etc.) of the relationship between items, and is therefore widely applicable.

  Here, the content includes, for example, music, movies, TV programs, media content such as a set of sentences, and merchandise.

  An item is a unit of information presentation and recommendation (recommendation) in the item introduction system 1, and its contents differ depending on the situation. For example, the unit may be an item such as an artist, an album, or a song for music, an individual work for a movie, a staff member such as a director, an actor, or a distribution company. In other words, it includes not only individual works / products but also a group that shares arbitrary attributes (metadata).

  For music, metadata is added to the content regardless of the user who experiences the content, such as the genre, the birthplace / debut year of the artist, the words that appear in the review text, and the features extracted from the content. All data that is or is contained.

  In FIG. 1, the item introduction system 1 is shown to be configured by one server (server 11), one network (network 10), and two clients (client 12 and client 13). However, the numbers of networks, servers, and clients are arbitrary, and a plurality of networks, a plurality of servers, or three or more clients may be provided. Further, for example, part of the processing on the server side may be performed between clients using P2P technology or the like.

  The network 10 is, for example, one or a plurality of networks represented by the Internet or a LAN (Local Area Network). The network 10 may be a wired network, a wireless network, or a network in which wired and wireless are mixed.

  The server 11 presents an item related to the item already presented to the client, a related item related to the reference item based on the item designated by the client, and the degree of relevance used for the presentation. Processing related to registration or processing related to remuneration to be paid when an introduction act is established.

  Each client operates independently of each other, performs processing related to the association between items to the server 11, and receives a reward when an introduction act based on the association is established. Independent of such processing, each client makes an item presentation request and receives a related item.

  In the following description, a client that performs processing related to the assignment of relevance is referred to as client 12, and a client that performs processing related to item presentation is described as client 13. In practice, these processes are independent of each other, so that one client may perform both of these processes or only one of them. Moreover, the execution timing of each process is arbitrary.

  Below, the role of each device in the item introduction system 1 will be described in more detail.

  As described above, in the item introduction system 1, roughly divided, three processes of association between items, item presentation, and reward distribution are performed.

  First, the association between items will be described. In the item introduction system 1, the association between items is pseudo-securitized and is performed based on the market principle.

  As will be described later, when the introduction of an item made based on an association between certain items satisfies a predetermined condition and the introduction act is established, a reward is paid to the user who made the association. Accordingly, the user of each client performs association for the purpose of obtaining the right to receive the reward. That is, the user of each client predicts the relationship between items that contribute to the establishment of the introduction act, and performs the association between the items.

  However, if the association is allowed in a disorderly manner, even if the association has a high degree of association, the reliability as information may be lowered. Therefore, in the item introduction system 1, the association between items that contributed to the establishment of the introduction act A predetermined amount of reward is distributed to the user who has performed the reward, and the received reward is different depending on the proportion of the relevance of the association between the items for which the reward is to be distributed. That is, as the number of associations (total number of associations) increases, the reward for one association decreases, and conversely, as the number of associations decreases, the reward for one association increases.

  In this way, a value is generated in the association between the items, and the value is determined by a trade-off between the number of reward opportunities and the amount of reward at one time.

  In addition, in the item introduction system 1, the association action is restricted between items and for each user. For example, the maximum number of associations made by each user and the maximum number of associations that can be made between items are limited. This maximum number may be variable. This further increases the value of the association between items.

  Furthermore, in the item introduction system 1, the relevance (right to perform association) between items is pseudo-securitized so that users can freely trade with each other. That is, in the item introduction system 1, an act of association is assumed as a prediction, and the relationship is securitized (considered as a related stock) so that a prediction market that can be freely traded based on the market principle is formed. ing.

  Therefore, the user of the client 12 performs processing related to acquisition of related stocks as the association between items to the server 11 (dotted arrow 21). The acquisition of the related stock may be newly acquired from the server 11 or may be acquired by a transaction with another user. The server 11 manages such predicted market transactions. Moreover, the server 11 reflects the loss which arises by the transaction on the user of the client who performed the transaction (dotted line arrow 24). Further, the server 11 also manages associations (relationships between items) performed between items in this way.

  FIG. 2 is a diagram schematically showing information related to the association between items managed by the server 11. In FIG. 2, items 31 to 35 indicate a plurality of items to be introduced in advance, and arrows 41 to 48 indicate relationships between items for which the client 12 has registered the degree of association. .

  As indicated by arrows 41 to 48, there is a bidirectional relationship between each of the items 31 to 35 from one to the other. For example, between the item 31 and the item 35, there is a relationship (arrow 42) from the item 31 to the item 35 and a relationship (arrow 48) from the item 35 to the item 31. Arrows 41 to 48 shown in FIG. 2 indicate such association between items.

  For example, when the user of the client 12 performs association in a relationship from the item 31 to the item 32, the server 11 registers and manages the association (arrow 41) in the database. Note that the server 11 calculates and manages the sum of relevances and the average value for each relationship (arrow) between items as necessary.

  Returning to FIG. 1, the client 13 that receives the item presentation makes an item presentation request (or a related item presentation request) to the server 11 independently of the above-described processing (dotted arrow 22). Based on this request, the server 11 searches the item related to the designated item or the item already presented from the information regarding the association between items as shown in FIG. Present (dotted arrow 23).

  For example, in a content sales service, when a user of a client purchases some content, a method of randomly searching for content to be purchased from a large amount of content prepared in advance requires complicated work for the user. In addition, it is not always possible to find satisfactory content that the user wishes to purchase, which may reduce the user's willingness to purchase.

  Further, even if the content seller introduces recommended content to the user, the user does not always like the content selected by the seller. Therefore, in the item introduction system 1, the server 11 causes the user to associate items with each other, grasps the user's preference by the action, and presents item information suitable for the user's preference.

  As a result, each user can refer to the presented item without searching for himself / herself, and can easily expand the range of contents to be considered for purchase. Many can be purchased.

  Thus, the server 11 of the item introduction system 1 introduces items to the client user.

  Furthermore, the server 11 determines that the introduction act has been established when a predetermined condition is satisfied, for example, the content is purchased based on the item introduction, and has contributed to the establishment of the introduction act. Dividends are distributed to users associated with the association, that is, the relationship between the items used to introduce the item that caused the purchase of the content (dotted arrow 24).

  The item introduction system 1 may be used for any service such as a content sales service, a content download service, a rental service, and a browsing service. Alternatively, the item introduction system 1 itself may be established as an introduction service.

  In the following, for simplification of description, the item introduction system 1 will be described as being used for a content sales service and introducing information about content as an item.

  FIG. 3 is a block diagram illustrating an internal configuration example of the server 11.

  In FIG. 3, a CPU (Central Processing Unit) 101 of the server 11 performs various processes according to a program stored in a ROM (Read Only Memory) 102 or a program loaded from a storage unit 113 to a RAM (Random Access Memory) 103. Execute the process. The RAM 103 also appropriately stores data necessary for the CPU 101 to execute various processes.

  The CPU 101, ROM 102, and RAM 103 are connected to each other via a bus 104. An input / output interface 110 is also connected to the bus 104.

  The input / output interface 110 includes an input unit 111 including a keyboard and a mouse, a display including a CRT (Cathode Ray Tube) and an LCD (Liquid Crystal Display), an output unit 112 including a speaker, and a hard disk. A communication unit 114 including a storage unit 113 and a modem is connected. The communication unit 114 performs communication processing via a network including the Internet.

  A drive 115 is connected to the input / output interface 110 as necessary, and a removable medium 121 such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory is appropriately attached, and a computer program read from them is It is installed in the storage unit 113 as necessary.

  FIG. 4 is a functional block diagram for explaining the functions of the CPU 101 that executes the program.

  As shown in FIG. 4, the CPU 101 is a predictive market processing unit 201 that manages the association between items based on the buying and selling behavior in the predictive market where the relationship between items is bought and sold, and the transaction of the predictive market, A related item presentation processing unit 202 that presents a related item to the user of the client 13 based on the association, and a dividend processing unit 203 that performs processing related to payment of a dividend (reward) when an introduction act to the user of the client 13 is established. Have

  The forecast market processing unit 201 receives from the client 12 a transaction request processing unit 211 that accepts a buy / sell order of related stocks indicating the relationship between items, and an instruction (buy / sell related stocks) supplied from the client 12. On the other hand, a relevance degree totaling unit 212 that performs new association or update is provided.

  The related item presentation processing unit 202 includes an information presentation request processing unit 221 that receives a request from the client 13, an item information presentation processing unit 222 that introduces a related item to the user of the client 13, and a similarity between items. It has the item similarity calculation part 223 to calculate.

  The payout processing unit 203 receives a content purchase instruction from the user of the client 13, purchase processing reception unit 231 that performs processing related to the purchase, regards the purchase of the content as establishment of the introduction act, and determines the amount of dividend for the establishment of the introduction act A payout calculating unit 232 for calculating, and a payout distribution processing unit 233 for distributing the calculated payout to users who have been given a relevance level that has contributed to the establishment of the introduction act.

  FIG. 5 is a schematic diagram illustrating an internal configuration example of the storage unit 113 in FIG. 3.

  As shown in FIG. 5, the storage unit 113 accumulates and manages information related to transactions between relationships (related stocks) between items in the forecast market, and stores information related to users of clients. It has a user information database 302 to be managed, an inter-item relevance database 303 for accumulating and managing relevance given between items, and an item information database 304 for accumulating and managing information on items to be introduced.

  Specific processing will be described below.

  First, an association between items, that is, a related stock transaction will be described. As described above, the item introduction system 1 uses the relationship between items as a stock (related stock), the degree of relevance indicating the amount of the relationship as a stock price, and the service as a trading place as a stock market (forecast market). In fact, client users can buy and sell related stocks. As a result, the value and interest regarding the association between items by the entire user are expressed as the degree of association, and the reliability of the association (or degree of association) as information increases. Therefore, the related item introduced based on the association (relation degree) is also more likely to be information more suitable for the user. That is, the server 11 can present items useful for the user.

  In addition, since the user can earn profit not only by the reward due to the establishment of the introduction act but also by buying and selling stocks (related stocks), the user's willingness to link between items can be improved, The database of the server 11 is likely to accumulate information useful for item introduction called relevance.

  The initial state between each item is a state in which no related stock is held by anyone. In an initial state, a certain number of related stocks (for example, 1000 stocks) can be purchased with a minimum unit (amount). After 1000 shares are bought in the smallest unit, buying and selling of stocks between users is started.

  First, the purchase of stock will be explained. The user of the client 12 who purchases the related stock places a purchase order with respect to the server 11. The server 11 executes a buy order process for processing the buy order. An example of the flow of the purchase order process will be described with reference to the flowchart of FIG. This will be described with reference to FIG. 7 as necessary.

When the buy order processing is started, the transaction request processing unit 211 of the forecast market processing unit 201 is supplied from the client 12 via the network 10 as shown in FIG. 7 (arrow of FIG. 7). 401) Accept a buy order. For example, the transaction request processing unit 211 obtains, from the user A, a purchase order for the related stock s _ij from the item Oi to the item Oj together with the number of stocks m _ij and the buy price b _ij thereof.

When accepting the buy order, the transaction request processing unit 211 obtains the current user point of the user of the client 12 from the user information database 302 in step S2 (arrow 402 in FIG. 7), and points using the user point A limit determination is performed, and in step S3, it is determined whether or not the point limit has been exceeded based on the result. For example, the transaction request processing unit 211 compares the user points currently held by the user A with the number of shares and a multiplier m _ij b _{ij of the} purchase price. In step S3, it is determined whether or not the limit has been exceeded. If it is determined that the limit is not exceeded, the transaction request processing unit 211 advances the process to step S4.

In step S4, the transaction request processing unit 211 accesses the relevance degree transaction database 301, acquires information on the current selling price and the number of shares of the related stock s _ij (arrow 403 in FIG. 7), and confirms the selling order. To do.

The transaction request processing unit 211 determines whether or not there is a sell order in step S5. If it is determined that there is a sell order, that is, the related stock that satisfies the buy order condition, that is, the related stock that is put on the sale below the buy price bij. If s _ij is present, the transaction is concluded, and the information is supplied to the relevance degree totaling unit 212 (arrow 404 in FIG. 7), and the process proceeds to step S6.

In step S <b> 6, the relevance degree totaling unit 212 calculates and updates the relevance degree as a result of the current transaction being established. The degree of association w _ij between the item Oi and the item Oj at a certain time is determined by the stock price of the stock s _ij corresponding to the relation between the items at that time. Here, the stock price is, for example, the sum of the bid prices of the shares currently held by the user divided by the number of shares, the average bid price of 10% of the total number of recently traded shares, and the pending selling order. It is the lowest price in the market. The relevance level totaling unit 212 stores the value proportional to the stock price as a new relevance level in the inter-item relevance level database 303 (arrow 405 in FIG. 7).

Further, in step S7, the degree-of-relevance totaling unit 212 updates the user holding stock based on the transaction result. As a result of the successful transaction, the relevance degree totaling unit 212 stores the number of stocks s _ij currently owned by the user A in the user information database 302 (arrow 406 in FIG. 7). In addition, the number of shares s _ij held by a group of users who have been selling shares bought by the user A (U _ij ^t : t is assumed to be a certain time) is reduced according to the number sold and the user information database. Save to 302. In step S8, the degree-of-relevance calculation unit 212 further subtracts the points associated with the related stock purchase from the user points held by the user u. At this time, points are added according to the number of shares sold from each of the user groups U _ij ^t at the time of purchase order of the user u. Here, the point is a unit of currency for stock transactions and dividends, but what kind of entity is given is arbitrary, and may depend on, for example, a system service. In the following, for convenience of explanation, explanation will be made with Japanese yen as a unit.

  When the user points are subtracted as described above, the relevance degree totaling unit 212 ends the purchase order process.

  Further, when it is determined in step S5 that there is no sell order, the transaction request processing unit 211 proceeds to step S9, and it is assumed that the transaction has not been completed, and a new sell order that satisfies the condition is entered. Is stored in the relevance degree transaction database 301 (arrow 405 in FIG. 7). When the buy order is stored, the transaction request processing unit 211 ends the buy order process.

  If it is determined in step S3 that the point limit has been exceeded, the transaction request processing unit 211 determines that the sale is not established and ends the purchase order process.

  Next, the selling order will be described. The user of the client 12 who sells related stocks places a selling order on the server 11. The server 11 executes sell order processing for processing the sell order. An example of the flow of the sell order process will be described with reference to the flowchart of FIG. Note that the flow of processing in the functional block is basically the same as that of the purchase order described with reference to FIG.

When the sell order process is started, the transaction request processing unit 211, in step S21, sends a sell order of the related stock s _ij to be associated from the item Oi to the item Oj from the client 12 (user B). _Accepted with _ij and its selling price b _ij .

When accepting the sell order, the transaction request processing unit 211 obtains the number of shares of the related stock s _ij currently held by the user B from the user information database 302 in step S22 and confirms whether or not it is larger than the number of ordered stocks m _ij. To do. In step S23, the transaction request processing unit 211 determines whether or not the number of shares is insufficient based on the confirmation result. If it is determined that the number of ordered shares is less than the number of owned shares, the transaction request processing unit 211 advances the process to step S24.

In step S24, the transaction request processing unit 211 accesses the relevance degree transaction database 301 to confirm the buy order, and inquires about the set of the current buy price of the related stock s _ij and the number of shares. In step S25, the transaction request processing unit 211 determines whether or not there is a buy order satisfying the selling order condition, that is, the selling price or more, and if it is determined that it exists, the process proceeds to step S26.

In step S <b> 26, the relevance level totaling unit 212 determines the relevance level according to the stock price resulting from the current transaction and stores it in the inter-item relevance level database 303. Further, in step S 27, the association degree totaling unit 212 updates the number of shares of s _ij currently held by the user B as a result of the transaction being established, and stores it in the user information database 302. Further, the relevance count unit 212 uses the number of shares of s _ij held by the user group (U _ij ^t : t is assumed to be a certain time) that has placed a buy order for the shares sold from the user B as the number of purchases. The user information database 302 is added accordingly.

In step S28, the relevance totaling unit 212 adds points for the sale to the points owned by the user B, and subtracts points from each of the user groups U _ij ^t according to the number of shares in the buy order, The calculation results are accumulated in the user information database 302, and the selling order process is terminated.

  Also, in step S25, if there is no buy order and the transaction is not completed, the transaction request processing unit 211 advances the process to step S29 and preferentially receives a new purchase order that satisfies the conditions. This sell order is stored in the relevance degree transaction database 301 in order to make it trade, and the sell order process is terminated. If it is determined in step S23 that the number of ordered shares is less than the number of owned shares and the number of shares is insufficient, the transaction request processing unit 211 terminates the selling order process as a trading failure.

  This will be described more specifically with reference to FIG. FIG. 9 shows the transition of information related to stocks stored in the relevance degree transaction database 301 in the trading of a certain related stock (related stock from item Oi to item Oj), and the user points, stocks held, and stock prices It shows the transition. In the example of FIG. 9, it is assumed that a predetermined number of stocks have already been bought by a plurality of users (including user u3, user u4, and user u5) in a minimum unit.

  In the initial state of FIG. 9, as shown in Table 411, no order is accumulated in the relevance degree transaction database 301, and as shown in the state 421, the stock price of 1000 shares is set to 1 yen. ing.

  In this initial state, as shown in the order 422, the user u1 places a buy order to buy 50 shares for 10 yen. At this time, as shown in Table 411, since there is no user who sells stocks, the buying order of the user u1 is stored in the buying order in the relevance degree transaction database 301. At this time, there is no change in the degree of association since the sale is not established.

  Next, as shown in the order 423, the user u2 places a buy order so as to buy 50 shares for 12 yen. Also in this case, as shown in Table 412, since there is no user who sells stocks, the buy order of the user u2 is stored in the buy order in the relevance degree transaction database 301. At this time as well, there is no change in the degree of relevance because trading is not established.

  Here, as shown in the order 424, the user u3 holding the related stock places a selling order to sell 30 stocks for 8 yen. At this time, as shown in Table 413, the user u1 and the user u2 place a purchase order, but the user u2 with the higher purchase price is given priority and can be bought at the selling price of the user u3. This priority may be reversed. Further, the transaction amount may be set to the price on the buy order side, the price on the sell order side, or in the meantime.

  As a result, as shown in Table 414, the user u2 obtains 30 shares and subtracts 240 yen from the holding points, and the user u3 transfers 30 shares and adds 240 yen to the holding points. In addition, since the total purchase price of the stock is 970 (for the holders other than the user u2 and the user u3) +240 (for the current transaction) = 1220 yen, the stock price = relevance is 1.21 yen.

  Further, as shown in the order 425, the user u4 holding the stock places a selling order so as to sell 50 shares for 12 yen. At this time, the user u1 and the user u2 place a buy order. First, the user u2 with a high buy price buys stock from the user u4 at the selling price of the user u4 of 12 yen. On the other hand, the buying price of the user u1 is 10 yen and does not reach the selling price of the user u4, so the user u1 cannot buy it. The amount not bought by the user u4 is stored as a selling order in the relevance degree transaction database 301 as shown in Table 415.

  As a result, as shown in Table 415, the user u2 acquires 20 shares and subtracts 240 yen from the holding points, and the user u4 transfers 20 shares and adds 240 yen to the holding points. In addition, the total purchase price of shares will be 950 + 240 (3. transactions) +240 (current transaction) = 1430 yen due to this transaction, so the stock price = relevance will be 1.43 yen.

  Further, as shown in the order 425, the user u5 who has held the stock places a selling order so that 100 shares are sold at 10 yen. At this time, user u1 can purchase 50 shares for 12 yen. The amount not bought by the user u5 is stored in the relevance degree transaction database 301.

  As a result, as shown in Table 416, the user u1 acquires 50 shares and subtracts 500 yen from the holding points, and the user u5 transfers 50 shares and adds 500 yen to the holding points. In addition, the total purchase price of stocks will be 900 + 240 (3. transactions) + 240 (4. transactions) + 500 (current transactions) = 1880 yen as a result of this transaction. Is 1.88 yen.

  As described above, the association between items (traded) based on the market principle is used for presentation of related items (item recommendation) by the server 11.

  An example of the flow of the presentation process executed by the server 11 for the client 13 requesting the presentation of items will be described with reference to the flowchart of FIG. This will be described with reference to FIG. 11 as necessary.

  When the presentation process is started, the information presentation request processing unit 221 of the related item presentation processing unit 202 sends an information presentation request supplied from the client 13 via the network 10 in step S41 as shown in FIG. Accept (arrow 431 in FIG. 11). When the information presentation request is received, the information presentation request processing unit 221 acquires information regarding the association between items stored in the inter-item relevance database 303 in step S42 (arrow 432 in FIG. 11), and the information is included in the information. Identify related items based on. Further, in step S43, the information presentation request processing unit 221 accesses the item information database 304, acquires the information of the item of the related source and the information of the item of the related destination (arrow 433 in FIG. 11). It supplies to the item information presentation process part 222 (arrow 434 of FIG. 11). In step S44, the item information presentation processing unit 222 generates presentation information for presenting information about related items to the user of the client 13 based on the information. In step S45, the item information presentation processing unit 222 By supplying to the client 13 via the network 10 (arrow 435 in FIG. 11), it is presented to the user of the client 13. When the presentation of the presentation information ends, the item information presentation processing unit 222 ends the presentation process.

  Next, the distribution of the payout when the introduction act is established (for example, when an item is purchased) will be described. As described above, in the item introduction system 1, when there is an action such as purchase of an item with reference to related item information, a dividend (reward) is paid to a user who holds the related stock. . By determining the dividend amount so as to be inversely proportional to the value of the relevance level, it is possible to provide an incentive for association, that is, contribution to stock trading.

  For example, related stocks with high stock prices are related items that are famous or popular (major), or combinations of items are very appropriate, so items can be purchased with reference to that information. (There are many opportunities for dividends) Therefore, one dividend should be small. On the other hand, even if a user associates between items that are less popular or notorious (minor), the association is unlikely to contribute to the establishment of the referral action, and there is a high possibility that there will be fewer opportunities for dividends. Becomes cheaper and easier to purchase, and if a single payout is large, it is highly incentive for the user. By doing in this way, it can suppress that the association of an item is biased among some items.

  An example of the flow of payout distribution processing for performing such payout calculation and distribution will be described with reference to the flowchart of FIG. This will be described with reference to FIG. 13 as necessary.

  When the payout distribution process is started, the payout processing unit 203 accepts a purchase process by the client 13 in step S61. As illustrated in FIG. 13, the payout processing unit 203 receives a purchase request for an item supplied from the user of the client 13 via the network 10 (arrow 441 in FIG. 13). At this time, after browsing the information of the item Oi, when the item Oj is reached from the item Oi using the related item information of the item Oj and finally the item Oj is purchased, the relationship between the item Oi and the item Oj is related. A dividend is generated for the user who holds the stock. That is, the process in step S61 is a process in which the payout processing unit 203 recognizes the occurrence of a payout. For example, if a payout is generated even when there is a transition of information presentation from the item Oi to the item Oj, This is a process for receiving an information presentation request.

  In step S62, the purchase process accepting unit 231 determines whether or not a payout is generated by the purchase process. If it is determined that the payout is generated, the purchase process receiving unit 231 supplies purchase process information to the payout calculating unit 232 (arrow 442 in FIG. 13). ), The process proceeds to step S63. In step S63, the dividend calculation unit 232 acquires information such as the stock price, the number of shares, and the purchase price from the relevance degree transaction database 301, the inter-item relevance degree database 303, and the item information database 304 (arrows 443 to arrow in FIG. 13). 445).

When each piece of information is acquired, the payout calculating unit 232 calculates a payout value based on the information in step S64. Related share price p _ij of items Oi and item Oj, the user of the number of shares held of the payout target s _ij ^u, Datosuruto price of the purchased item Oj is Pj, for example, αP _j s _ij ^u / p _ij is the dividend amount Become. This payout may depend on either Pj or w ^u _ij , or may be a constant value without depending on both. Further, it may be linked to the price of the related link source item Oi.

  When the payout is calculated, the payout calculating unit 232 supplies the result to the payout distribution processing unit 233 (arrow 446 in FIG. 13). In step S65, the payout distribution processing unit 233 accesses the user information database 302 and updates the user points using the payout (arrow 447 in FIG. 13).

  For example, assume that the related stock s12 from the item O1 to the item O2 is traded as shown in FIG. 9, and the user u1 and the user u2 each hold 50 shares. At this time, the price of the item O2 is 1000 yen, the multiplication rate (α above) is 0.001, and after viewing the information on the item O1, a user browses the information on the item O2 based on the related item information. When the purchase is decided, 0.001 × 1000 × 50 / 1.88 = 26.6 yen is paid out to the user u1 and the user u2.

  When the update is completed, the payout distribution processing unit 233 ends the payout distribution process. If it is determined in step S62 that no payout is generated, the purchase process accepting unit 231 ends the payout distribution process.

  The server 11 may not only present the related item according to the above-described association (relation degree), but may also present the related item by using metadata attached to the item together. By using the metadata, it is possible to present an item whose relevance is not determined by the market (the linked stock is not purchased).

  An example of the flow of the presentation process in that case will be described with reference to the flowchart of FIG. Description will be made with reference to FIGS. 15 to 18 as necessary.

  In step S81, the information presentation request processing unit 221 of the related item presentation processing unit 202 receives an information presentation request for requesting information presentation of some item Oi supplied from the client 13 via the network 10 (arrow in FIG. 15). 451). When receiving the information presentation request, the information presentation request processing unit 221 notifies the item similarity calculation unit 223 of the request (arrow 452 in FIG. 15).

  In step S82, the item similarity calculation unit 223 accesses the inter-item relevance database 303, acquires information on the relevance regarding the item Oi (arrow 453 in FIG. 15), and further accesses the item information database, Item metadata is acquired (arrow 454 in FIG. 15).

  In step S83, the item similarity calculation unit 223 calculates the item similarity based on the information. The item similarity r is obtained, for example, by using the following formula (1) obtained by calculating the Euclidean distance by metadata and multiplying the reciprocal by the (normalized) relevance.

In equation (1), vector v _ih is the value of the h-th element of the vector representation of the metadata of item Oi. The distance measure related to metadata may not be the Euclidean distance, but may be a cosine distance, an intercity distance, or the like. In addition to this, any function for obtaining the similarity may be used as long as it monotonically increases the relevance and monotonically decreases the distance based on the metadata. In the case of a pair of items for which the relevance is not determined, for example, the average r of all relevances may be used as the temporary relevance, and the similarity r obtained using the above equation (1) may be used.

  In step S84, the item similarity calculation unit 223 specifies a similar item based on the calculation result. Here, several items that are strongly related to the item Oi are selected as similar items.

  The item information presentation processing unit 222 creates presentation information in step S85, and presents the presentation information to the user by supplying the presentation information to the client 13 via the network 10 in step S86. (Arrow 456 in FIG. 15).

  When the presentation of the presentation information ends, the item information presentation processing unit 222 ends the presentation process.

For example, assuming that items 1 to 4 are given metadata (meta 1 to meta 5) expressed numerically as in the table shown in FIG. 16, Euclidean for item 1 to item 2 to item 4 is given. The similarity based on the reciprocal of the distance is as shown in the table shown in FIG. Therefore, when items are arranged in order of similarity (in descending order of similarity), item 2, item 3, and item 4 are obtained. Further, when the degree of relevance according to the market is w ₁₂ = 4.4, w ₁₃ = 2.1, and w ₁₄ = 2.3, when the weighted similarity r as in the above equation (1) is obtained, FIG. It will look like a squeezed table. Therefore, when items are arranged in order of similarity (in descending order of similarity), item 2, item 4, and item 3 are obtained.

  As described above, by using the market principle for association between items, as a result, related items reflecting the opinions of many users are presented. In addition, since dividends are determined according to the degree of relevance, it becomes an incentive to grant relevance (stock purchase) to items with a low degree of popularity and popularity (minor), and as a result, related items are presented for a wide range of items It becomes possible.

  Furthermore, by determining the degree of similarity together with metadata, it is possible to present related items even for items for which no degree of association is given, and at the same time, the objective similarity between the user's subjective similarity and metadata Related items reflecting both similarities can be presented.

  As described above, the server 11 can make a more desirable recommendation to the client user.

  The series of processes described above can be executed by hardware or can be executed by software. When the above-described series of processing is executed by software, a program constituting the software is installed from a network or a recording medium.

  For example, as shown in FIG. 3, the recording medium is distributed to distribute a program to a user separately from the apparatus main body, and includes a magnetic disk (including a flexible disk) on which a program is recorded, an optical disk ( Removable media 121 such as CD-ROM (compact disk-read only memory), DVD (including digital versatile disk), magneto-optical disk (including MD (mini-disk) (registered trademark)), or semiconductor memory In addition to being configured, it is configured by a ROM 102 on which a program is recorded, a hard disk included in the storage unit 113, and the like that are distributed to the user in a state of being pre-installed in the apparatus main body.

  In the present specification, the step of describing the program recorded on the recording medium is not limited to the processing performed in chronological order according to the described order, but is not necessarily performed in chronological order. It also includes processes that are executed individually.

  Further, in this specification, the system represents the entire apparatus composed of a plurality of devices (apparatuses).

  In the above description, the configuration described as one device may be divided and configured as a plurality of devices. Conversely, the configurations described above as a plurality of devices may be combined into a single device. Of course, configurations other than those described above may be added to the configuration of each device. Furthermore, if the configuration and operation of the entire system are substantially the same, a part of the configuration of a certain device may be included in the configuration of another device. That is, the embodiment of the present invention is not limited to the above-described embodiment, and various modifications can be made without departing from the gist of the present invention.

  The present invention can be applied to an information processing apparatus.

It is a block diagram which shows the structural example of the item introduction system to which this invention is applied. It is a schematic diagram explaining the association between items. It is a block diagram which shows the structural example of the server of FIG. It is a functional block diagram explaining the function which CPU of a server has. It is a figure which shows the structural example of a memory | storage part. It is a flowchart explaining the example of the flow of a purchase order process. It is a figure which shows the example of the mode of operation | movement of the functional block regarding a purchase order process. It is a flowchart explaining the example of the flow of a sell order process. It is a figure which shows the example of the mode of a related stock transaction. It is a flowchart explaining the example of the flow of a presentation process. It is a figure which shows the example of the mode of operation | movement of the functional block regarding a presentation process. It is a flowchart explaining the example of the flow of a dividend distribution process. It is a figure which shows the example of the mode of operation | movement of the functional block regarding a payout distribution process. It is a flowchart explaining the other example of the flow of a presentation process. It is a figure which shows the other example of the mode of operation | movement of the functional block regarding a presentation process. It is a table | surface which shows the example of the metadata of an item. It is a table | surface which shows the example of the similarity degree by the data collected from the item 1. It is a table | surface which shows the example of the similarity which reflected the related degree.

Explanation of symbols

  DESCRIPTION OF SYMBOLS 1 Item introduction system, 11 Server, 12 Client, 13 Client, 201 Forecast market processing part, 202 Related item presentation processing part, 203 Dividend processing part, 211 Transaction request processing part, 212 Relevance degree totaling part, 221 Information presentation request processing part , 222 Item information presentation processing unit, 223 Item similarity calculation unit, 231 Purchase processing reception unit, 232 Dividend calculation unit, 233 Dividend distribution processing unit, 301 Relevance transaction database, 302 User information database, 303 Inter-item relevance database, 304 Item information database

Claims (6)

An information processing apparatus that provides a user with a service that introduces a related item related to the item from a predetermined item as a reference,
The relationship between the items is a stock, a transaction using the consideration of the stock performed by users, and a management means for managing the relationship between the items updated by the transaction,
An information processing apparatus comprising: presentation means for determining the related item from a predetermined item based on the relevance managed by the management means and presenting the related item to the user. A payout means for distributing a payout according to the amount of the stock to a user who has made an association corresponding to the association when a predetermined condition is satisfied based on the related item presented by the presentation means The information processing apparatus according to claim 1. Determining means for determining a related item based on both the relevance managed by the management means and the metadata of the item;
The information processing apparatus according to claim 1, wherein the presenting unit presents the related item determined by the determining unit. An information processing method for an information processing apparatus that provides a user with a service that introduces a related item related to the item from a predetermined item as a reference,
The relationship between the items is a stock, a transaction using the consideration of the stock performed by users, and a management step for managing the relationship between the items updated by the transaction,
An information processing method comprising: a presentation step of determining the related item from a predetermined item as a reference based on the relevance managed by the processing of the management step and presenting the related item to the user. A computer-executable program for controlling a process of providing a user with a service that introduces a related item related to the item from a predetermined item as a reference,
The relationship between the items is a stock, a transaction using the consideration of the stock performed by users, and a management step for managing the relationship between the items updated by the transaction,
A program for causing a computer to execute a presenting step of determining the related item from a predetermined item as a reference based on the relevance managed by the process of the managing step and presenting the related item to the user.   A recording medium on which the program according to claim 5 is recorded.

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