| 摘要 |
PROBLEM TO BE SOLVED: To widely recommend contents such as contents that a user is inexperienced in. SOLUTION: A matrix generation part 18 generates a meta-data matrix consisting of rows corresponding to N meta-data and columns corresponding to M contents. An LSA arithmetic part 20 subjects the meta-data matrix to singular value decomposition processing to generate its approximate matrix. A vector arithmetic part 22 clusters M column components of the approximate matrix into S clusters to generate an UPV for every S clusters. The vector arithmetic part 22 selects one or more groups of representative vectors of two clusters out of representative vectors of S clusters and generates a difference UPV between UPVs of the two clusters as to the selected one or more groups. A content recommendation part 23 recommends contents by using the difference UPV. This invention is applicable to an information processor recommending contents. COPYRIGHT: (C)2006,JPO&NCIPI
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