Data mining method from text database based on fuzzy quantification analysis

Keisuke Aoki, Junzo Watada

    研究成果: Conference contribution

    2 被引用数 (Scopus)

    抄録

    Recently, various types of data are expected to get in information processing according to multi-media technology. Especially, linguistic data are employed in fuzzy systems as well as fuzzy numerical values. In this paper we propose a text minig method based on fuzzy quantification model. In the process of text mining, we will pursue the following steps: 1) Sentences included in a text in Japanese are broken down into words. 2) It is possible to realize common understanding using fuzzy thesaurus that enables us to translate words into synonyms or into upper concepts. In this paper, we employ the method to translate words using Chinese characters or continuous letters of Katakana more then one katakana letter (Japanese alphabet letter) into keywords. The method realizes the high speed of processing without any dictionary for separating words. Fuzzy multivariate analysis is employed to analyze such processed data and to abstract a latent mutual related structure under the data. In other words, we abstract the knowledge from the given text data. At the end we apply the method to mining the text information of libraries and Web pages distributed over a web network and discussing about the application to Kansei engineering.

    本文言語English
    ホスト出版物のタイトルConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
    ページ6472-6478
    ページ数7
    7
    DOI
    出版ステータスPublished - 2004
    イベント2004 IEEE International Conference on Systems, Man and Cybernetics, SMC 2004 - The Hague
    継続期間: 2004 10 102004 10 13

    Other

    Other2004 IEEE International Conference on Systems, Man and Cybernetics, SMC 2004
    CityThe Hague
    Period04/10/1004/10/13

    ASJC Scopus subject areas

    • Engineering(all)

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