Abstract: A data processing method, includes: mapping each of a plurality of data, for which classes the data belong to are known, to one point on an N-dimensional feature space using at least two feature amounts; dividing a set of points corresponding to the plurality of data mapped on the feature space into a plurality of N-dimensional simplexes having each point as an apex; classifying a set of points that constitute a hyperplane of each simplex obtained by the division into a subset including points that belong to the same class as elements; and reducing the elements of the subsets for each of the classified subsets. The dividing includes dividing the set of points into the plurality of simplexes so a hypersphere circumscribed on each simplex does not include a point that constitutes another simplex.

Abstract: To provide a contents creating device and a contents creating method capable of distributing contents having an article arrangement with high relativity to a user as distribution destination. A contents creating device 100 to create contents to be distributed within a predetermined group, including a material evaluation unit 130 configured to evaluate relativity of material data of contents to a user as contents distribution destination, and a contents editing unit 140 configured to determine an article arrangement within contents according to an evaluation, wherein contents based on the article arrangement are created. Due to this, it is possible to distribute contents having an article arrangement with high relativity to a user of the distribution destination and it is possible for the user as distribution destination to browse an article in which the user is highly interested.

Abstract: Extraction of scenes of interest from video content is disclosed, which includes: collecting comments from a comment server, which contain keywords associated with the video content; segmenting the video content into scenes; measuring the number of ones of the comments which were posted for each scene, as a post count; detecting ones of the scenes, each of which has the post count equal to or larger than a predetermined number, as a plurality of scenes of interest; extracting, per each scene-of-interest, at least one of the keywords which is contained in the comments with a number equal to or larger than a pre-selected number, as a comment keyword; and tagging each scene of interest with the comment keyword, per each scene-of-interest.

Abstract: Extraction of scenes of interest from video content is disclosed, which includes: collecting comments from a comment server, which contain keywords associated with the video content; segmenting the video content into scenes; measuring the number of ones of the comments which were posted for each scene, as a post count; detecting ones of the scenes, each of which has the post count equal to or larger than a predetermined number, as a plurality of scenes of interest; extracting, per each scene-of-interest, at least one of the keywords which is contained in the comments with a number equal to or larger than a pre-selected number, as a comment keyword; and tagging each scene of interest with the comment keyword, per each scene-of-interest.

Abstract: Provided are techniques which offer an advantage of reduced time and reduced storage capacity required to calculate the feature value of AAC-format song data. A feature extraction unit includes: an MDCT coefficient extraction unit which extracts MDCT coefficients from AAC-format song data; a classification unit which locates the MDCT coefficients thus extracted by the MDCT coefficient extraction unit on Mel frequency regions so as to uniformly classify the MDCT coefficients into classes, the number of which is the same as that of a predetermined number of Mel filter banks; an integrating unit which extracts the MDCT coefficients classified by the classification unit by applying a predetermined window function, and integrates the MDCT coefficients thus extracted, in increments of the Mel filter banks; and a feature calculation unit which calculates the feature value by performing logarithmic cosine conversion of the integrated results obtained by the integrating unit.

Abstract: A discussion enlivenment assistance device includes: a state visualization unit which generates discussion state data displaying index values indicating a state of each discussion site; a user characteristic presentation unit which generates participating user characteristic data in relation to users participating in a discussion site specified by a user, the participating user characteristic data displaying index values indicating profiles of the users in a discussion; a user control unit which generates invitation nominated user data displaying an invitation nominated user appropriate for the discussion site specified by the user; and a display unit which displays the discussion state data, the participating user characteristic data, and the invitation nominated user data.

Abstract: An apparatus for retrieving music that matches with a user preference across a plurality of music is provided. The apparatus comprises a feature vector generating device for generating feature vectors of each of the music, a clustering device for clustering the music into a plurality of clusters according to the feature vectors, a music extraction device for extracting a predetermined number of music from each of the clusters, a music selection accepting device for accepting a selection of music by the user from the music, and a music retrieval device for calculating similarities between a feature vector of the selected music and feature vectors of each of the music, and retrieving music that have higher similarities to the selected music among the music.

Abstract: To provide a contents creating device and a contents creating method capable of distributing contents having an article arrangement with high relativity to a user as distribution destination. A contents creating device 100 to create contents to be distributed within a predetermined group, including a material evaluation unit 130 configured to evaluate relativity of material data of contents to a user as contents distribution destination, and a contents editing unit 140 configured to determine an article arrangement within contents according to an evaluation, wherein contents based on the article arrangement are created. Due to this, it is possible to distribute contents having an article arrangement with high relativity to a user of the distribution destination and it is possible for the user as distribution destination to browse an article in which the user is highly interested.

Abstract: A query building module 6 includes a query DB 61 for managing a query vector of a piece of music, which matches a user preference, a similarity calculating unit 62 for calculating a similarity between the query vectors, which are registered in the query DB 61, a query vector integrating unit 63 for integrating a plurality of query vectors similar to each other into one piece of preference information, and a query updating unit 64 for newly registering the integrated new query vector to the query DB 61 and deleting the integrated two similar query vectors from the query DB 61, thereby updating the query DB 61, and builds a query Q in which all of the query vectors having high similarity are integrated and is an aggregation of the query vectors not similar to each other.

Abstract: To provide a query extracting apparatus, query extracting method and query extracting program capable of retrieving an image that is suited to a part of lyrics while also having suitability for the other parts, a query extracting apparatus 100 to retrieve images suited to lyrics divides lyrics targeted for query extraction into a plurality of segments, determines a preferential segment in which a keyword group is preferentially selected from among the segments, and selects a keyword group to retrieve an image suited to lyrics of the preferential segment while also referring to information of one or more segments. By this means, keywords suited to the preferential segment are preferentially selected, while also referring to the other segments to extract an image retrieval query, and it is thus possible to retrieve an image that is suited to a part of the lyrics while also having suitability for the other parts.

Abstract: Provided are techniques which offer an advantage of reduced time and reduced storage capacity required to calculate the feature value of AAC-format song data. A feature extraction unit includes: an MDCT coefficient extraction unit which extracts MDCT coefficients from AAC-format song data; a classification unit which locates the MDCT coefficients thus extracted by the MDCT coefficient extraction unit on Mel frequency regions so as to uniformly classify the MDCT coefficients into classes, the number of which is the same as that of a predetermined number of Mel filter banks; an integrating unit which extracts the MDCT coefficients classified by the classification unit by applying a predetermined window function, and integrates the MDCT coefficients thus extracted, in increments of the Mel filter banks; and a feature calculation unit which calculates the feature value by performing logarithmic cosine conversion of the integrated results obtained by the integrating unit.

Abstract: It is an object to provide user classification apparatus, a user classification method, and a program used thereby, which classify users based on search log and support the analysis of customer trends, and advertisement distribution apparatus, an advertisement distribution method, and a program used thereby, which distribute advertisements based on the analysis of customer trends. The user classification apparatus is provided with a search log database, a user search log information extracting unit extracting search log information of a user, an analyzed keyword extracting unit extracting search keyword information contained in search log information, a search session dividing unit dividing the search log information of the user into a plurality of search sessions, a search session class extracting unit generating a class, a user belonging class calculation unit classifying the user into the class, and a user search log analysis result display unit displaying the classification result.

Abstract: An apparatus for retrieving music that matches with a user preference across a plurality of music is provided. The apparatus comprises a feature vector generating device for generating feature vectors of each of the music, a clustering device for clustering the music into a plurality of clusters according to the feature vectors, a music extraction device for extracting a predetermined number of music from each of the clusters, a music selection accepting device for accepting a selection of music by the user from the music, and a music retrieval device for calculating similarities between a feature vector of the selected music and feature vectors of each of the music, and retrieving music that have higher similarities to the selected music among the music.

Abstract: The present invention provides a content distribution system capable of improving user convenience and effectively distributing content for trial listening. A terminal apparatus includes: a content database that stores plural kinds of content data for trial listening received from a content distribution server; a usage history information recording unit that records usage history information of a user; a user preference estimating unit that estimates user preference on the basis of the usage history information of the user recorded in the usage history information recording unit, and generates preference information; a content extracting unit that calculates similarity between the preference information and each of the content data for trial listening stored in the content database, and extracts content data for trial listening having high similarity from the content database; and a content data playing unit that plays the extracted content data for trial listening.

Abstract: Degrees of association between categories of songs (hereinafter, song categories) corresponding to information showing advertisement distribution target categories and distribution object advertisements are determined in advance in an advertisement DB. A song categorization module calculates degrees of association between an acoustic feature amount of a song being played (hereinafter, current song) and feature amounts of the song categories, and a song-related distribution object advertisement candidate group extraction module determines a distribution object advertisement corresponding to a song category with a high degree of association is determined as a distribution object advertisement. An advertisement presentation module provides information on the distribution object advertisement to a user along with current song information.

Abstract: A query building module 6 includes a query DB 61 for managing a query vector of a piece of music, which matches a user preference, a similarity calculating unit 62 for calculating a similarity between the query vectors, which are registered in the query DB 61, a query vector integrating unit 63 for integrating a plurality of query vectors similar to each other into one piece of preference information, and a query updating unit 64 for newly registering the integrated new query vector to the query DB 61 and deleting the integrated two similar query vectors from the query DB 61, thereby updating the query DB 61, and builds a query Q in which all of the query vectors having high similarity are integrated and is an aggregation of the query vectors not similar to each other.

Abstract: In a shot segmentation process 11 and a section extraction process 12 in a training process, a training data is segmented into shot and specific sections are extracted. In a training process 14 for a story segmentation point recognizing device for entire video, a story segmentation point recognizing device for entire video is produced. In a training process 15 for a story segmentation point recognizing device for specific sections, story segmentation point recognizing device for specific sections is produced. In an evaluation process, the story segmentation points in entire input data and the story segmentation points in specific sections are recognized so that the story segmentation points of the input data are provided by integrating the both segmentation results.