| Presentation | 2004/11/27 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) KENTARO NAGAI, HO TU BAG, |
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| PDF Download Page | PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | 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 relation-ships 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. |
| Keyword(in Japanese) | (See Japanese page) |
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| Paper # | AI2004-23 |
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| Committee | AI |
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| Conference Date | 2004/11/27(1days) |
| Place (in Japanese) | (See Japanese page) |
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| Topics (in Japanese) | (See Japanese page) |
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| Registration To | Artificial Intelligence and Knowledge-Based Processing (AI) |
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| Language | ENG |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | 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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| 1st Author's Name | KENTARO NAGAI |
| 1st Author's Affiliation | School of Knowledge Science, Japan Advanced Institute of Science and Technology() |
| 2nd Author's Name | HO TU BAG |
| 2nd Author's Affiliation | School of Knowledge Science, Japan Advanced Institute of Science and Technology |
| Date | 2004/11/27 |
| Paper # | AI2004-23 |
| Volume (vol) | vol.104 |
| Number (no) | 485 |
| Page | pp.pp.- |
| #Pages | 6 |
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