Mining from Semi-structured Data and Knowledge Integration (データベースシステム 研究報告 特集:空間メディアとGIS,および一般)

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概要

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• Despite the growing popularity of semi-structured data such as Web documents, most knoledge discovery research has focused on databases containing well structured data. In this paper, we try to find useful information from semi-structured data. In our approach, we begin by representing semi-structured data in a prototype-based approach, then detect the typical structure of object sets. Next, we apply the algorithm of mining association rules to structured layer by using the idea of concept hierarchy. Furthermore, relationships between concepts are defined and data values are not only generalized but also specialized for more flexible knowledge mining.

• 一般社団法人情報処理学会の論文
• 2000-01-24

著者

• Uehara Kuniaki

  Research Center For Urban Safety And Security Kobe University

• Uehara Kuniaki

  Research Center For Urban Safety & Security Kobe University

• Maruyama Kohei

  Graduate School Of Science And Technology Kobe University

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• Mining from Semi-structured Data and Knowledge Integration (データベースシステム 研究報告 特集:空間メディアとGIS,および一般)
• Mutual Knowledge Use between Mining from Semi-Structured Data and Information Extraction Using HMM

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