Sparse substring pattern set discovery using linear programming boosting

Kazuaki Kashihara, Kohei Hatano, Hideo Bannai, Masayuki Takeda

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

抜粋

In this paper, we consider finding a small set of substring patterns which classifies the given documents well. We formulate the problem as 1 norm soft margin optimization problem where each dimension corresponds to a substring pattern. Then we solve this problem by using LPBoost and an optimal substring discovery algorithm. Since the problem is a linear program, the resulting solution is likely to be sparse, which is useful for feature selection. We evaluate the proposed method for real data such as movie reviews.

元の言語英語
ホスト出版物のタイトルDiscovery Science - 13th International Conference, DS 2010, Proceedings
ページ132-143
ページ数12
DOI
出版物ステータス出版済み - 12 20 2010
イベント13th International Conference on Discovery Science, DS 2010 - Canberra, ACT, オーストラリア
継続期間: 10 6 201010 8 2010

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
6332 LNAI
ISSN(印刷物)0302-9743
ISSN(電子版)1611-3349

その他

その他13th International Conference on Discovery Science, DS 2010
オーストラリア
Canberra, ACT
期間10/6/1010/8/10

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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  • これを引用

    Kashihara, K., Hatano, K., Bannai, H., & Takeda, M. (2010). Sparse substring pattern set discovery using linear programming boosting. : Discovery Science - 13th International Conference, DS 2010, Proceedings (pp. 132-143). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 巻数 6332 LNAI). https://doi.org/10.1007/978-3-642-16184-1_10