Shigeyuki Tomita

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This paper proposes a recommendation method that focuses on not only predictive accuracy but also serendipity. On many of the conventional recommendation methods, items are categorized according to their attributes (a genre, an authors, etc.) by the recommender in advance, and recommendation is made using the results of the categorization. In this study,(More)
Many real problems with uncertainties may often be formulated as Stochastic Programming Problem. In this study, Genetic Algorithm (GA) which has been recently used for solving mathematical programming problem is expanded for use in uncertain environments. The modified GA is referred as GA in uncertain environments (GAUCE). In the method, the objective(More)
This paper presents an application of the idea called concept for realizing more appropriate representation of human preferences. In the previous study, we proposed the new information recommendation method. Concretely, items for recommendation were selected using the idea of concept, which are impressions of users on items inferred using tagging data of a(More)
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