Inner Product Space Based on Fuzzy Neighborhoods for Text Data Analysis

• KAWASAKI Yuichi

  University of Tsukuba

• MIYAMOTO Sadaaki

  University of Tsukuba

Bibliographic Information

Other Title

• ファジィ近傍に基づく内積空間とカーネル法によるテキストデータ解析
• ファジィ キンボウ ニ モトズク ナイ セキ クウカン ト カーネルホウ ニ ヨル テキストデータ カイセキ

Abstract

A fuzzy neighborhood model to analyze text data is proposed. This method can represent a sequencial structure in a set of texts, while traditional methods like the vector space model cannot as it simply counts the number of words in a text. Moreover fuzzy neighborhood model is a generalization of the vector space model and fuzzy equivalence relations. An advantage of this model is that it provides a positive definite kernel for data analysis. Accordingly we apply the present model to text analysis using kernel c-means clustering and kernel principal component analysis. Two examples of analysis of newspaper articles and medical incident reports are shown.

Journal

• Journal of Japan Society for Fuzzy Theory and Intelligent Informatics

  Journal of Japan Society for Fuzzy Theory and Intelligent Informatics 21 (4), 461-469, 2009

  Japan Society for Fuzzy Theory and Intelligent Informatics

Keywords

• Fuzzy Neighborhood
• Fuzzy Equivalence Relation
• Kernel Function
• Kernel PCA

Details

• CRID: 1390282680164461056
• NII Article ID: 10025994797
• NII Book ID: AA1181479X
• DOI: 10.3156/jsoft.21.461
• ISSN: 18817203
• ISSN: 13477986
• NDL BIB ID: 10405989
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I10405989
• Text Lang: ja
• Data Source:
  • JaLC
  • NDL
  • Crossref
  • CiNii Articles
  • KAKEN
• Abstract License Flag: Disallowed