An Estimation of Difficulty for Academic Books using Reviews

• Nakayama Yuki

  Kanazawa University Graduate School of Natural Science & Technology

• Nambo Hidetaka

  Kanazawa University Graduate School of Natural Science & Technology

• Kimura Haruhiko

  Kanazawa University Graduate School of Natural Science & Technology

Bibliographic Information

Other Title

• レビュー情報を用いた学術本の難易度推定

Abstract

A collaborate filtering has been generally used as a method which recommends items to customers. However, recommending academic books, it need to consider difficulty of them and individual amount of knowledge as well as user's preference. If the recommendation method considers only user's preference, they might regret after buying or reading recommended book because it won't match user's appropriate level. In this paper, we focus on academic books and propose a method which estimates the difficulty of academic books using user's reviews. Estimating difficulty of books will support users to search and recommend academic books that match user's skill. Moreover, we evaluated applying our method to academic text books about C programming Language. We verified that our method is more effective than traditional methods for academic books.

Journal

• Transactions of the Japanese Society for Artificial Intelligence

  Transactions of the Japanese Society for Artificial Intelligence 27 (3), 213-222, 2012

  The Japanese Society for Artificial Intelligence

Keywords

• information retrieval
• difficulty
• learning support
• recommender system

Details

• CRID: 1390001205106712704
• NII Article ID: 130001878759
• NII Book ID: AA11579226
• DOI: 10.1527/tjsai.27.213
• BIBCODE: 2012TJSAI..27..213N
• ISSN: 13468030
• ISSN: 13460714
• Web Site: https://www.jstage.jst.go.jp/article/tjsai/27/3/27_3_213/_pdf
• Text Lang: ja
• Data Source:
  • JaLC
  • Crossref
  • CiNii Articles
  • KAKEN
• Abstract License Flag: Disallowed