Presentation | 2007-01-23 P/N Classification for Reputation Extraction from BBS Keisuke TAKEUCHI, Akira URASIMA, Minoru HATADA, Shoryu ATAKA, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | This paper reports on the P/N classification system for the documents that include reputation information. The P/N classification system divides documents into positive and negative ones. We employ 3 words (adjective or adjective noun, noun prior them and posterior negative expression "nai") dictionary while past study employ one word (adjective or adjective noun) dictionary. The dictionary entries has own score calculated by Training data and P/N Classification is derived from them. The result of the experiment was that the success rate was 78.5% in past study and 87.5% in our study. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Reputation extraction / Text mining / Document classification / Scoring |
Paper # | KBSE2006-64 |
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Committee | KBSE |
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Conference Date | 2007/1/16(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (in Japanese) | (See Japanese page) |
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Paper Information | |
Registration To | Knowledge-Based Software Engineering (KBSE) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | P/N Classification for Reputation Extraction from BBS |
Sub Title (in English) | |
Keyword(1) | Reputation extraction |
Keyword(2) | Text mining |
Keyword(3) | Document classification |
Keyword(4) | Scoring |
1st Author's Name | Keisuke TAKEUCHI |
1st Author's Affiliation | Toyama Prefectural University() |
2nd Author's Name | Akira URASIMA |
2nd Author's Affiliation | Toyama Prefectural University |
3rd Author's Name | Minoru HATADA |
3rd Author's Affiliation | Toyama Prefectural University |
4th Author's Name | Shoryu ATAKA |
4th Author's Affiliation | Toyama Prefectural University |
Date | 2007-01-23 |
Paper # | KBSE2006-64 |
Volume (vol) | vol.106 |
Number (no) | 473 |
Page | pp.pp.- |
#Pages | 6 |
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