| Presentation | 1999/7/22 Independent Topic Analysis : Extraction of Characteristic Topics by maximization of Independence Yasusi Sinohara, |
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| PDF Download Page | PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| 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. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Indpendent Component Analysis / Topic Extraction / Text Retrieval / Dual Scaling |
| Paper # | AI99-26 |
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| Conference Information | |
| Committee | AI |
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| Conference Date | 1999/7/22(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
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| Paper Information | |
| Registration To | Artificial Intelligence and Knowledge-Based Processing (AI) |
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| 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 | |