Multi-view clustering with web and linguistic features for relation extraction

Yulan Yan, Haibo Li, Yutaka Matsuo, Zhenglu Yang, Mitsuru Ishizuka

研究成果: Conference contribution

抜粋

Binary semantic relation extraction is particularly useful for various NLP and Web applications. Currently Webbased methods and Linguistic-based methods are two types of leading methods for semantic relation extraction task. With a novel view on integrating linguistic analysis on local text with Web frequent information, we propose a multi-view coclustering approach for semantic relation extraction. One is feature clustering by automatically learning clustering functions for Web features, linguistic features simultaneously based on a subset of entity pairs. The other is relation clustering, using the feature clustering functions to define learning function for relation extraction. Our experiments demonstrate the superiority of our clustering approach comparing with several state-of-theart clustering methods.

元の言語English
ホスト出版物のタイトルAdvances in Web Technologies and Applications - Proceedings of the 12th Asia-Pacific Web Conference, APWeb 2010
ページ140-146
ページ数7
DOI
出版物ステータスPublished - 2010
外部発表Yes
イベント12th International Asia Pacific Web Conference, APWeb 2010 - Busan
継続期間: 2010 4 62010 4 8

Other

Other12th International Asia Pacific Web Conference, APWeb 2010
Busan
期間10/4/610/4/8

    フィンガープリント

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications

これを引用

Yan, Y., Li, H., Matsuo, Y., Yang, Z., & Ishizuka, M. (2010). Multi-view clustering with web and linguistic features for relation extraction. : Advances in Web Technologies and Applications - Proceedings of the 12th Asia-Pacific Web Conference, APWeb 2010 (pp. 140-146). [5474142] https://doi.org/10.1109/APWeb.2010.64