Improvement of Information Filtering by Independent Components Selection

• Yokoi Takeru

  Graduate School of Engineering, Osaka Prefecture University

• Yanagimoto Hidekazu

  Graduate School of Engineering, Osaka Prefecture University

• Omatu Sigeru

  Graduate School of Engineering, Osaka Prefecture University

Bibliographic Information

Other Title

• 独立成分の選択による情報推薦の改良
• ドクリツ セイブン ノ センタク ニ ヨル ジョウホウ スイセン ノ カイリョウ

Abstract

We propose an improvement of an information filtering system with independent components selection. The independent components are obtained by Independent Component Analysis and considered as topics. It is effective for improving accuracy of information filtering to select some similar topics by focusing on these meaning. To achieve this, we select the topics by Maximum Distance Algorithm with Jensen-Shannon divergence. In addition, document vectors are represented by the selected topics. We create a user profile from transformed data with a relevance feedback. Finally, we recommend documents by the user profile and evaluate the accuracy by imputation precision. We carry out an evaluation experiment to confirm availability of the proposed method and also consider the meaning of components in this experiment.

Journal

• IEEJ Transactions on Electronics, Information and Systems

  IEEJ Transactions on Electronics, Information and Systems 126 (4), 492-497, 2006

  The Institute of Electrical Engineers of Japan

Keywords

• Information Filtering
• Independent Component Analysis
• Maximum Distance Algorithm

Details

• CRID: 1390282679582224000
• NII Article ID: 10017539381
• NII Book ID: AN10065950
• DOI: 10.1541/ieejeiss.126.492
• ISSN: 13488155
• ISSN: 03854221
• NDL BIB ID: 7911601
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I7911601
• Web Site: https://www.jstage.jst.go.jp/article/ieejeiss/126/4/126_4_492/_pdf
• Text Lang: ja
• Data Source:
  • JaLC
  • NDL
  • Crossref
  • CiNii Articles
  • KAKEN
• Abstract License Flag: Disallowed