タイトル | Document Classification Method with Small Training Data |
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著者 | 前田康成 、吉田秀樹 、松嶋敏泰 |
年度 | 2009 |
形式 | 国際学会 |
分野 | 知識情報処理 |
掲載雑誌名 | ICROS-SICE International Joint Conference 2009 |
掲載号・ページ | pp.138-141, Fukuoka, Japan |
掲載年 | 2009 |
掲載月 | 8 |
アブスト (日本語) |
学会名:ICROS-SICE International Joint Conference 2009 日程:August 18(Tue.)-21(Fri.), 2009 場所:Fukuoka International Congress Center, Fukuoka, JAPAN 査読有 DOI: 無し |
アブスト (英語) |
Document classification is one of important topics in the field of NLP(Natural Language Processing). In our previous research we've proposed a document classification method which minimizes an error rate with reference to a Bayes criterion. But when the number of documents in training data is small, the accuracy of the previous method is low. So in this research we propose a document classification method whose accuracy is higher than the previous method when the number of documents in training data is small. |
備考 (日本語) |
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備考 (英語) |
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論文原稿 | ダウンロード |
発表資料 |