Abstract: In a processing system 101, a first processing device 111 obtains first characteristics information indicating a characteristics of users in a first environment, divides the users into first clusters according to the first characteristics information, and transmits, to a second processing device 121, belonging information indicating which of the first clusters each of the users belongs to. The second processing device 121 obtains second characteristics information indicating characteristics of the users in a second environment, and divides the users into second clusters according to the belonging information and the second characteristics information.

Abstract: An information processing apparatus acquires user features indicating features for each of a plurality of users and item features indicating features for each of a plurality of items, acquires time-series information indicating time-series interactions between the plurality of users and the plurality of items, constructs, based on the user features, the item features, and the time-series information, a graph including a plurality of user nodes representing the plurality of users, a plurality of item nodes representing the plurality of items, and links indicating interaction relationships in the plurality of user nodes and the plurality of item nodes, and extracts, from the graph, a node representation in the graph for any node among the plurality of user nodes and the plurality of item nodes.

Abstract: An information processing apparatus acquires factual features of each of a plurality of users as user features, creates a relationship graph showing a social relationship between the plurality of users based on the user features, sets a target user among the users, sets at least one user related to the target user among the plurality of users as a related user based on the relationship graph, and estimates an attribute of the target user based on the user feature of the target user and the user feature of the related user.

Abstract: An information processing apparatus selects, from a plurality of users, a model user group and a target user group that is different from the model user group, generates, for each user of the target user group, a user representation representing relationships with the plurality of users and the plurality of items, and predicts, based on the user representation, one or more users that have features similar to those of users included in the model user group, from the target user group, as a similar user group.

Abstract: An information processing apparatus acquires factual features of each of a plurality of users as user features, creates a relationship graph indicating a social relationship among the plurality of users based on the user features, sets a target user among the plurality of users, and predicts a disease risk indicating the risk of developing at least one predetermined disease for the target user, based on the relationship graph and the user feature of the target user.

Abstract: Provided is a technique for realizing targeting in which social connections are considered. An information processing apparatus acquires factual features of each of a plurality of users as user features, and based on the user features, creates a relationship graph showing a social relationship between the plurality of users, sets one or more users among the plurality of users as a target user group, and based on the relationship graph and the user features of the target user group, adds one or more users, among the plurality of users, having a social relationship with a user included in the target user group to the target user group and determines the resulting target user group as an expanded user group.

Abstract: An information processing apparatus acquires a factual feature of each of a plurality of users as user features, acquires features regarding a plurality of items as item features from a predetermined database, constructs, based on the user features and the item features, a graph including a plurality of user nodes representing the plurality of users, a plurality of item nodes representing the plurality of items, and links indicating mutual relationships between the plurality of user nodes and the plurality of item nodes, and extracts a node representation, in the graph, of any node of the plurality of user nodes and the plurality of item nodes from the graph.

Abstract: In a processing system 101, a first processing device 111 obtains first characteristics information indicating characteristics of users in a first environment, divides the users into first clusters according to the first characteristics information, and transmits, to a second processing device 121, representation information representing characteristics of users belonging to each of the first clusters using a centroid vector based on the first characteristics information of the cluster. The second processing device 121 obtains second characteristics information indicating characteristics of the users in a second environment, and divides the users into second clusters according to the representation information and the second characteristics information.

Abstract: In a processing system 101, a first processing device 111 obtains first characteristics information indicating characteristics of users in a first environment, divides the users into first clusters according to the first characteristics information, and transmits, to a second processing device 121, representation information representing characteristics of users belonging to each of the first clusters using a centroid vector based on the first characteristics information of the cluster. The second processing device 121 obtains second characteristics information indicating characteristics of the users in a second environment, and divides the users into second clusters according to the representation information and the second characteristics information.

Abstract: In a processing system 101, a first processing device 111 obtains first characteristics information indicating a characteristics of users in a first environment, divides the users into first clusters according to the first characteristics information, and transmits, to a second processing device 121, belonging information indicating which of the first clusters each of the users belongs to. The second processing device 121 obtains second characteristics information indicating characteristics of the users in a second environment, and divides the users into second clusters according to the belonging information and the second characteristics information.

Abstract: A category highly relevant to a keyword combination including a plurality of keywords is extracted. An information processing apparatus extracts a category where the number of times when the category is specified as a search condition along with a first keyword is greater than or equal to a first threshold value from among a plurality of categories that are hierarchized in a tree structure. Subsequently, from among categories corresponding to descendants of the extracted category, the information processing apparatus extracts a category where the number of times when the category is specified as a search condition along with a second keyword is greater than or equal to a second threshold value as a category relevant to a combination of the first keyword and the second keyword.

Abstract: To associate a keyword with a category having a high degree of relevance with the keyword. An association apparatus comprises an acquisition means that acquires the number of times when each of a plurality of categories of a search target is designated as a search condition together with a keyword, and a registration means that registers category information indicating the category for which the number of times acquired by the acquisition means is a threshold or more, and the keyword in an associated manner.

Abstract: A character string which is set in advance is stored (S4), and display data are obtained (S5), and link information is extracted from the obtained display data (S9), and a partial link character string is generated from the extracted link information (S10), and similarity of the character string and the partial link character string is calculated (S11), and a determination is made as to whether the link information is similar link information on the basis of the calculated similarity (S12), and when the link information is determined to be the similar link information, a display position 42 where the extracted link information is displayed is specified, and a display area (43, 44) for displaying existence information indicating existence of the similar link information is specified on the basis of the specified display position (S13), and the existence information indicating existence of the similar link information is displayed in the specified display area (S15).

Abstract: A search query including a search word entered by the user is obtained (S4), the obtained search query is stored in association with user identification information and acquisition time of the search query into a search query log DB 12a (S5). In the case where a predetermined user operation is detected, search queries corresponding to the user identification information of the user are extracted (S6). A first search query is specified from the extracted search queries (S7), a second search query whose acquisition time is earlier than acquisition time of the first search query is specified from the extracted search queries (S8 and S9). A search word in the first search query and a search word in the second search query are registered as related words into a related-word DB 12b (S10).

Abstract: An information processing apparatus determines a threshold value of the number of times of use of a keyword on the basis of the number of times of use of the keyword in each unit period included in a cycle period. Next, the information processing apparatus identifies a period in which the numbers of times of use exceeds the threshold value in the cycle period as a candidate of a popularity period of the keyword. Next, the information processing apparatus excludes the identified period from the popularity period if a situation in which the numbers of times of use in the identified period exceed the threshold value is different from a situation based on a periodic popularity of the keyword. When the identified candidate period is not excluded from the popularity period, the information processing apparatus determines the identified period to be the popularity period.

Abstract: A category highly relevant to a keyword combination including a plurality of keywords is extracted. An information processing apparatus extracts a category where the number of times when the category is specified as a search condition along with a first keyword is greater than or equal to a first threshold value from among a plurality of categories that are hierarchized in a tree structure. Subsequently, from among categories corresponding to descendants of the extracted category, the information processing apparatus extracts a category where the number of times when the category is specified as a search condition along with a second keyword is greater than or equal to a second threshold value as a category relevant to a combination of the first keyword and the second keyword.

Abstract: An information processing apparatus determines a threshold value of the number of times of use of a keyword on the basis of the number of times of use of the keyword in each unit period included in a cycle period. Next, the information processing apparatus identifies a period in which the numbers of times of use exceeds the threshold value in the cycle period as a candidate of a popularity period of the keyword. Next, the information processing apparatus excludes the identified period from the popularity period if a situation in which the numbers of times of use in the identified period exceed the threshold value is different from a situation based on a periodic popularity of the keyword. When the identified candidate period is not excluded from the popularity period, the information processing apparatus determines the identified period to be the popularity period.

Abstract: To associate a keyword with a category having a high degree of relevance with the keyword. An association apparatus comprises an acquisition means that acquires the number of times when each of a plurality of categories of a search target is designated as a search condition together with a keyword, and a registration means that registers category information indicating the category for which the number of times acquired by the acquisition means is a threshold or more, and the keyword in an associated manner.

Abstract: A search query of a search word entered by the user is received, the received search queries are stored in accordance with reception order, a preceding search query whose reception order is earlier than that of the received search query is extracted on the basis of a preset search query extracting condition, a preceding search word constructing the extracted preceding search query and a search word constructing the received search query are stored as a character string set, a character string set having the search word which is the same or similar to the preceding search word is extracted in accordance with a preset character string set extraction start condition (S51), a character set as a related word is specified from the extracted character string set on the basis of a preset registration condition (S53), and the specified character string set is registered as related words into a related-word database (S54).

Abstract: A search query of a search word entered by the user is received, the received search queries are stored in accordance with reception order, a preceding search query whose reception order is earlier than that of the received search query is extracted on the basis of a preset search query extracting condition, a preceding search word constructing the extracted preceding search query and a search word constructing the received search query are stored as a character string set, a character string set having the search word which is the same or similar to the preceding search word is extracted in accordance with a preset character string set extraction start condition (S51), a character set as a related word is specified from the extracted character string set on the basis of a preset registration condition (S53), and the specified character string set is registered as related words into a related-word database (S54).