Abstract: An information processing system according to one embodiment includes a first specifying unit, a second specifying unit, a generation unit, and an output unit. The first specifying unit specifies one or more first evaluation points of view corresponding to an expression in first information created by a provider of an object based on dictionary data indicating association between an expression and an evaluation point of view. The second specifying unit specifies one or more second evaluation points of view corresponding to the expression in second information created by a reviewer for the object based on the dictionary data. The generation unit generates supplementary information based on a difference in an evaluation degree between the first evaluation point of view and the second evaluation point of view. The output unit outputs the supplementary information.

Abstract: A computer system interconnected to a community of users having a data processor input module programmed to receive communications from said users including one or more inputs regarding food recipes and store said inputs in accessible memory. A data processor determining module programmed to access stored data and to apply a data interpretative algorithm to said data to unify and organize disparate data inputs into a cohesive database relating to recipes. Also, a search entry module connected to the recipe database to permit access to the database to support a search algorithm applied to the database.

Abstract: An information processing system according to one embodiment includes a first specifying unit, a second specifying unit, a generation unit, and an output unit. The first specifying unit specifies one or more first evaluation points of view corresponding to an expression in first information created by a provider of an object based on dictionary data indicating association between an expression and an evaluation point of view. The second specifying unit specifies one or more second evaluation points of view corresponding to the expression in second information created by a reviewer for the object based on the dictionary data. The generation unit generates supplementary information based on a difference in an evaluation degree between the first evaluation point of view and the second evaluation point of view. The output unit outputs the supplementary information.

Abstract: A recommendation information presentation device includes a topic generation unit that mechanically classifies words extracted from text information about a plurality of products and generates a plurality of topics made up of a plurality of words, a product profile generation unit that generates a product profile indicating the tendency of distribution of words contained in the text information about products over topics, a presentation unit that presents words contained in at least two topics to a user terminal for each topic, an extraction unit that generates a user profile indicating the tendency of selection of a topic by a user based on selection of a topic by the user and extracts a product profile indicating the tendency of distribution that coincides with the tendency of selection with a certain degree or higher, and a recommendation information presentation unit that presents information about a product associated with the extracted product profile.

Abstract: One exemplary aspect comprises a computer system comprising: (a) a preprocessing unit that extracts text from a webpage to produce at least a first set of candidate keywords, applies language processing to produce at least a second set of candidate keywords, and combines said first and second sets of candidate keywords into a first candidate pool; (b) a candidate extraction unit that receives data from said preprocessing unit describing at least said first candidate pool and produces a second candidate pool; (c) a feature extraction unit that receives data describing at least said second candidate pool and analyzes said second candidate pool for general features and linguistic features; and (d) a classification unit that receives said data describing at least said second candidate pool and related data from said feature extraction unit, and determines a likelihood of each candidate in said second candidate pool being a primary or secondary keyword.

Abstract: The present disclosure is directed to a computer system and method performed by a selectively programmed data processor for providing data to a Web page such that items are presented to the user in a way that imitates a real world shopping experience. Various aspects of the disclosed technology also relate to systems and methods for calculating product or category associations using associative relation extraction. Additional aspects of the disclosed technology relate to automatic topic discovery, and event and category matching.

Abstract: A computer system interconnected to a community of users having a data processor input module programmed to receive communications from said users including one or more inputs regarding food recipes and store said inputs in accessible memory. A data processor determining module programmed to access stored data and to apply a data interpretative algorithm to said data to unify and organize disparate data inputs into a cohesive database relating to recipes. Also, a search entry module connected to the recipe database to permit access to the database to support a search algorithm applied to the database.

Abstract: The present disclosure is directed to a computer system and method performed by a selectively programmed data processor for providing data to a Web page such that items are presented to the user in a way that imitates a real world shopping experience. Various aspects of the disclosed technology also relate to systems and methods for calculating product or category associations using associative relation extraction. Additional aspects of the disclosed technology relate to automatic topic discovery, and event and category matching.

Abstract: One exemplary aspect comprises a computer system comprising: (a) a preprocessing unit that extracts text from a webpage to produce at least a first set of candidate keywords, applies language processing to produce at least a second set of candidate keywords, and combines said first and second sets of candidate keywords into a first candidate pool; (b) a candidate extraction unit that receives data from said preprocessing unit describing at least said first candidate pool and produces a second candidate pool; (c) a feature extraction unit that receives data describing at least said second candidate pool and analyzes said second candidate pool for general features and linguistic features; and (d) a classification unit that receives said data describing at least said second candidate pool and related data from said feature extraction unit, and determines a likelihood of each candidate in said second candidate pool being a primary or secondary keyword.