Association Rule Mining From Textual Data using Passages(Text Mining I)

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概要

• 論文の詳細を見る

• Discovering knowledge from large amount of textual data is an important problem. Especially, application of association rule mining to textual data has been studied excessively. Many works has successfully found relationships between words that reflects syntactical rules, co-occurences, or phrases. These rules are useful for understanding the liguistic nature, but in real life, the relationships between the topics or contents are important and useful, such as what kind of topic tends to appear in same paper or books. Our objective is to find relationships between contexts or topics. In this paper, we propose an approach to use passages to take in some level of semantics in rule mining. We show some preliminary results to show its potential and give discussions on the problem for further improvement.

• 一般社団法人情報処理学会の論文
• 2004-12-04

著者

• Nagai Kentaro

  School Of Knowledge Science Japan Advanced Institute Of Science And Technology

• Bao Ho

  School Of Knowledge Science Japan Advanced Institute Of Science And Technology

関連論文

• Association Rule Mining From Textual Data using Passages(Text Mining I)
• Association Rule Mining From Textual Data using Passages(Text Mining I)(Joint Workshop of Vietnamese Society of AI, SIGKBS-JSAI, ICS-IPSJ, and IEICE-SIGAI on Active Mining)

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