Abstract: An object is to provide a clustering system capable of performing clustering of a plurality of types of items to be able to recommend an item whose corresponding textual data exists but relational data with another type of item does not exist, to the other type of item. A first clustering means 3001 performs clustering of first IDs, based on the relational data. A second clustering means 3002 performs clustering of second IDs, based on the relational data and textual data associated with the second IDs. A topic assignment means 3003 assigns a topic for each word included in textual data corresponding to each second ID. A parameter decision means 3004 decides a parameter used for first clustering processing, a parameter used for second clustering processing, and a parameter used for topic assignment processing. The processing described above is repeated until it is determined that a predetermined condition is satisfied.

Abstract: There is provided an automatic negotiation system capable of generating an indicator for defining a favorable target candidate for a supplier. A supply utility function generation means 53 generates a supply utility function expressing a change in profit and loss of the supplier relative to a change in a total demand for each current time and future time. A demand utility function generation means 55 generates a demand utility function expressing a change in profit and loss of the supplier relative to a change in a demand of a consumer for each current time and future time.

Abstract: A learning means 71 learns, on the basis of learning data including a table including a meaning of a column, and a meaning of the table, a model indicating regularity between a distribution of attribute values according to the meaning of the column in the table and the meaning of the table. An estimating means 72 estimates, on the basis of a distribution of attribute values according to a meaning of a column in an input table and the model, a meaning of the table.

Abstract: Provide a stock management device capable of providing both a benefit of online shopping and a benefit by using a mobile sales vehicle. This stock management device is provided with: management means for managing stock information about stock of an item held by each of a plurality of mobile sales vehicles; first reception means for receiving, from each of the plurality of mobile sales vehicles, sales information indicating an item sold at a storefront of the mobile sales vehicle; second reception means for receiving, from a customer terminal, order information including information about an item ordered based on the stock information transmitted to the customer terminal; and transmission means for transmitting the order information to the mobile sales vehicle holding the ordered item included in the order information, wherein the management means updates the stock information based on at least one of the sales information and the order information.

Abstract: Provide a stock management device capable of providing both a benefit of online shopping and a benefit by using a mobile sales vehicle, and also being capable of delivering, to a customer doing online shopping, an item which the customer wants, even when the item is purchased at a mobile sales vehicle. This stock management device is provided with: management means for managing stock information about stock of an item held by each of a plurality of mobile sales vehicles; first reception means for receiving sales information; second reception means for receiving order information; transmission means for transmitting the order information to the mobile sales vehicle; and detection means for detecting the item included in the order information becoming out-of-stock, wherein, when the item becoming out-of-stock is detected, the transmission means transmits the order information to another mobile sales vehicle.

Abstract: Provide a stock management device capable of bringing both a benefit of online shopping and a benefit by using a mobile sales vehicle to a customer purchasing an item by online shopping. This stock management device is provided with: management means for managing stock information about stock of an item held by each of a plurality of mobile sales vehicles performing mobile sale; first reception means for receiving sales information indicating and current position information; second reception means for receiving order information and desired delivery time information and delivery address information; first specification means for specifying a mobile sales vehicle capable of delivering the item by the desired delivery time; first transmission means for transmitting the stock information and transmitting the stock information; and second transmission means for transmitting the order information, wherein the management means updates the stock information.

Abstract: Provide a stock management device enables a customer purchasing an item by online shopping to understand sales status of an item at a mobile sales vehicle. This stock management device is provided with: management means for managing stock information about stock of an item held by each of a plurality of mobile sales vehicles; first reception means for receiving sales information indicating an item sold at a storefront and state information indicating a state of the mobile sales vehicle; first transmission means for transmitting sales state information indicating whether or not the mobile sales vehicle is selling an item and the stock information, the sales state information being generated based on the state information; second reception means for receiving order information including information about an item ordered; and second transmission means for transmitting the order information to the mobile sales vehicle, wherein the management means updates the stock information.

Abstract: A co-clustering system capable of further improving prediction accuracy of a prediction model for each cluster is provided. Based on first master data, second master data, and fact data indicating a relation between a first ID which is an ID of a record in the first master data and a second ID which is an ID of a record in the second master data, the co-clustering means 71 executes co-clustering processing of co-clustering the first IDs and the second IDs. The prediction model generation means 72 executes prediction model generation processing of generating a prediction model for each cluster of at least the first ID. The determination means 73 determines whether or not a predetermined condition is satisfied. The prediction model generation processing and the co-clustering processing are repeated until it is determined that the predetermined condition is satisfied.

Abstract: There is provided a grouping system capable of defining groups of customers with similar purchase trends with high accuracy and defining groups of products or product-related items in terms of similar purchase trends, or groups of services or service-related items in terms of similar purchase trends with high accuracy. A purchase trend calculation means 3 calculates a trend of a customer to purchase a product per combination of customer and product or per combination of customer and product-related item as item related to a product on the basis of customers' product purchase situations. A grouping means 4 defines groups of customers and defines groups of products or groups of product-related items on the basis of the trends and a distribution of the trends.

Abstract: An object logical node achieved by a distributed data management device includes a storage unit for storing object node identifiers each uniquely assigned to a plurality of logical nodes, a storage unit for storing at least one of a plurality of partial data units, a link table for storing link information between the object logical node and a link destination logical node, a storage unit for storing a value range boundary value with respect to each attribute corresponding to the partial data unit, and a storage unit for storing a tree structure data unit with respect to each attribute including a plurality of tree nodes each indicating a value range for identifying the logical node storing the partial data unit corresponding to an access request, the tree structure data unit including a root tree node including at least one entry formed with a pointer pointing to a child tree node associated with the link destination logical node and a value indicating a value range for selecting the pointer.

Abstract: Provided is a grouping system capable of determining a group of products so that groups of the products likely to be simultaneously purchased can be grasped. A storage means 71 stores at least a purchasing context that is information indicating one or more types of products purchased in one purchasing activity. A grouping means 72 uses a likelihood of a combination of a group of the purchasing contexts, a group of the products, and a distribution parameter of a purchasing result, calculated by using the purchasing result corresponding to the combination of the group of the purchasing contexts, the group of the products, and the distribution parameter of the purchasing result, to determine the group of the purchasing contexts, the group of the products, and the distribution parameter of the purchasing result.

Abstract: A learning means 71 learns, based on learning data containing the meaning of a column in a table and the meaning of the table, a model indicating regularity between the meaning of the column in the table and the meaning of the table. An estimation means 72 estimates the meaning of the table based on the meaning of a column of a table to be input and the model.

Abstract: A prediction system capable of predicting an unknown value of an attribute with high accuracy is provided. Based on first master data, second master data, and fact data indicating a relation between a first ID which is an ID of a record in the first master data and a second ID which is an ID of a record in the second master data, the co-clustering means 81 co-clusters the first IDs and the second IDs. The prediction model generation means 82 generates a prediction model for each cluster of the first ID output from the co-clustering means 81. When the first ID and the objective variable which is one of the attributes included in the first master data are specified, the prediction means 83 predicts the value of the objective variable corresponding to the first ID based on the prediction model and the belonging probability that the first ID belongs to each cluster.

Abstract: A table operation system capable of altering the configuration of a table such that a condition for obtaining easily analyzable information can be designated is provided. A data acquiring means 72 specifies individual tables to serve as reference destinations of designated respective foreign key columns and, for each combination of key values in primary key columns of the specified individual tables, acquires a total value of relation values in a designated relation value column. A grouping means 73 groups the respective key values in the primary key columns of the individual tables on the basis of the total value acquired for each combination of the key values in the primary key columns of the individual tables and a statistical model of a designated type. An attribute value column adding means 74 adds, to each individual table, an attribute value column of which attribute value is identification information on a group to which each key value in each primary key column of each individual table belongs.

Abstract: Provided is a grouping system capable of grouping customers and options in each channel, considering variation of behavior of each customer depending on the channel. A grouping means 3 uses a likelihood of a group of customers, a group of options in a first channel, and a group of options in a second channel, calculated based on a distribution parameter of a history of the activity according to a combination of the group of customers and the group of options in the first channel, a history of the activity in the first channel, a distribution parameter of a history of the activity according to a combination of the group of customers and the group of options in the second channel, and a history of the activity in the second channel, to determine the group of customers, the group of options in the first channel, and the group of options in the second channel.

Abstract: To reduce a communication load among data storage devices and data processing devices, a communication device comprises node information storage means for storing identifiers of data devices and processing devices and communication costs, and search processing means for receiving a message, which includes a transfer route of message and a total cost, which is a communication cost of transfer route, and detecting and outputting a closed path, from transfer route, having a negative total cost, or transmitting to the registered data device a message including a new total cost calculated by subtracting a communication cost corresponding to data device concerned from total cost and a new transfer route made by adding communication device to transfer route, and transmitting to the registered processing device a message including a new total cost calculated by adding a communication cost corresponding to processing device concerned to total cost, and new transfer route.

Abstract: An object logical node achieved by a distributed data management device includes a storage unit for storing object node identifiers each uniquely assigned to a plurality of logical nodes, a storage unit for storing at least one of a plurality of partial data units, a link table for storing link information between the object logical node and a link destination logical node, a storage unit for storing a value range boundary value with respect to each attribute corresponding to the partial data unit, and a storage unit for storing a tree structure data unit with respect to each attribute including a plurality of tree nodes each indicating a value range for identifying the logical node storing the partial data unit corresponding to an access request, the tree structure data unit including a root tree node including at least one entry formed with a pointer pointing to a child tree node associated with the link destination logical node and a value indicating a value range for selecting the pointer.

Abstract: An information system includes a plurality of data storage servers that manage a data constellation in a distributed manner, an ID assigning unit (112) that assigns logical identifiers to the plurality of data storage servers on a logical identifier space, a range determination unit (114) that correlates a distribution of data in the data constellation with the logical identifier space so as to determine a range of values of the data corresponding to the logical identifier, and a destination resolving unit (340) that obtains, when searching for the destination of a node which stores any data having any attribute value or any attribute range, a logical identifier corresponding to a range of an attribute value space of the data which matches at least a part of the attribute value or the attribute range, on the basis of a correspondence relation among the range of values of the data, the logical identifier, and the destination address, with respect to each of the data storage servers, and determines the destinat

Abstract: A space-filling curve processing system includes a data density acquisition unit (104) that, when performing processing on a subspace of a multi-dimensional space, refers to distribution information indicating the density distribution or cumulative distribution of a data constellation of a plurality of one-dimensional values obtained by performing space-filling curve processing on multi-dimensional data associated with a processing objective, and acquires the data density of a one-dimensional value or range corresponding to the subspace, a determination unit (106) that determines whether to perform space-filling curve processing in accordance with the data density of the subspace, and a space-filling curve processing unit (108) that performs the space-filling curve processing in accordance with a determination result of the determination unit (106).

Abstract: An information system (1) includes a plurality of data storage servers (106) that manage a data constellation in a distributed manner, the plurality of data storage servers (106) respectively having destination addresses, a destination table management unit (400) that assigns a logical identifier to each of the data storage servers (106) on a logical identifier space, correlate a range of values of data in the data constellation with the logical identifier space, and determines a range of the data of each data storage server (106) in correlation with the logical identifier of each data storage server (106), and a destination resolving unit (340) that obtains the logical identifier corresponding to a range of the data which matches an attribute value on the basis of a correspondence relation among the range of the data, the logical identifier, and the destination address of each data storage server (106), and determines the destination address of the data storage server (106) corresponding to the logical ident