Presentation 1999/7/22
Independent Topic Analysis : Extraction of Characteristic Topics by maximization of Independence
Yasusi Sinohara,
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Abstract(in English) Topic plays important role in organizing/retrieving/summarizing documents in a document database. Especially, the topics characterizing groups of documents in the database are useful. We define these characteristic topics as independent topics and propose the mothod called "Dual Scaling Type Indpendent Component Analysis" to find them. We also show the method find the independent groups of documents and words characterized by the found topics combining the reduction of dimensionality by dual scaling.
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Keyword(in English) Indpendent Component Analysis / Topic Extraction / Text Retrieval / Dual Scaling
Paper # AI99-26
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Conference Information
Committee AI
Conference Date 1999/7/22(1days)
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Registration To Artificial Intelligence and Knowledge-Based Processing (AI)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Independent Topic Analysis : Extraction of Characteristic Topics by maximization of Independence
Sub Title (in English)
Keyword(1) Indpendent Component Analysis
Keyword(2) Topic Extraction
Keyword(3) Text Retrieval
Keyword(4) Dual Scaling
1st Author's Name Yasusi Sinohara
1st Author's Affiliation Communication and Information Research Laboratory Central Research Institute of Electric Power Industry()
Date 1999/7/22
Paper # AI99-26
Volume (vol) vol.99
Number (no) 225
Page pp.pp.-
#Pages 8
Date of Issue