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Efficient Classification with Conjunctive Features
https://ipsj.ixsq.nii.ac.jp/records/79540
https://ipsj.ixsq.nii.ac.jp/records/7954091c854c3-3e47-4288-91c3-b9a3a036c2aa
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
IPSJ-JNL5212046 (607.9 kB)
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Copyright (c) 2011 by the Information Processing Society of Japan
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| オープンアクセス | ||
| Item type | Journal(1) | |||||||||
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| 公開日 | 2011-12-15 | |||||||||
| タイトル | ||||||||||
| タイトル | Efficient Classification with Conjunctive Features | |||||||||
| タイトル | ||||||||||
| 言語 | en | |||||||||
| タイトル | Efficient Classification with Conjunctive Features | |||||||||
| 言語 | ||||||||||
| 言語 | eng | |||||||||
| キーワード | ||||||||||
| 主題Scheme | Other | |||||||||
| 主題 | 特集：情報爆発時代におけるIT基盤技術 | |||||||||
| 資源タイプ | ||||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||||||
| 資源タイプ | journal article | |||||||||
| 著者所属 | ||||||||||
| Institute of Industrial Science, the University of Tokyo | ||||||||||
| 著者所属 | ||||||||||
| Institute of Industrial Science, the University of Tokyo | ||||||||||
| 著者所属(英) | ||||||||||
| en | ||||||||||
| Institute of Industrial Science, the University of Tokyo | ||||||||||
| 著者所属(英) | ||||||||||
| en | ||||||||||
| Institute of Industrial Science, the University of Tokyo | ||||||||||
| 著者名 |
Naoki, Yoshinaga
× Naoki, Yoshinaga
× Masaru, Kitsuregawa
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| 著者名(英) |
Naoki, Yoshinaga
× Naoki, Yoshinaga
× Masaru, Kitsuregawa
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| 論文抄録 | ||||||||||
| 内容記述タイプ | Other | |||||||||
| 内容記述 | This paper proposes a method that speeds up a classifier trained with many conjunctive features: combinations of (primitive) features. The key idea is to precompute as partial results the weights of primitive feature vectors that represent fundamental classification problems and appear frequently in the target task. A prefix tree (trie) compactly stores the primitive feature vectors with their weights, and it enables the classifier to find for a given feature vector its longest prefix feature vector whose weight has already been computed. Experimental results on base phrase chunking and dependency parsing demonstrated that our method speeded up the SVM and LLM classifiers by a factor of 1.8 to 10.6. ------------------------------ This is a preprint of an article intended for publication Journal of Information Processing(JIP). This preprint should not be cited. This article should be cited as: Journal of Information Processing Vol.20(2012) No.1 (online) DOI http://dx.doi.org/10.2197/ipsjjip.20.228 ------------------------------ |
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| 論文抄録(英) | ||||||||||
| 内容記述タイプ | Other | |||||||||
| 内容記述 | This paper proposes a method that speeds up a classifier trained with many conjunctive features: combinations of (primitive) features. The key idea is to precompute as partial results the weights of primitive feature vectors that represent fundamental classification problems and appear frequently in the target task. A prefix tree (trie) compactly stores the primitive feature vectors with their weights, and it enables the classifier to find for a given feature vector its longest prefix feature vector whose weight has already been computed. Experimental results on base phrase chunking and dependency parsing demonstrated that our method speeded up the SVM and LLM classifiers by a factor of 1.8 to 10.6. ------------------------------ This is a preprint of an article intended for publication Journal of Information Processing(JIP). This preprint should not be cited. This article should be cited as: Journal of Information Processing Vol.20(2012) No.1 (online) DOI http://dx.doi.org/10.2197/ipsjjip.20.228 ------------------------------ |
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| 書誌レコードID | ||||||||||
| 収録物識別子タイプ | NCID | |||||||||
| 収録物識別子 | AN00116647 | |||||||||
| 書誌情報 |
情報処理学会論文誌 巻 52, 号 12, 発行日 2011-12-15 |
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| ISSN | ||||||||||
| 収録物識別子タイプ | ISSN | |||||||||
| 収録物識別子 | 1882-7764 | |||||||||
