Extracting keyphrases to represent relations in social networks from web

Junichiro Mori, Mitsuru Ishizuka, Yutaka Matsuo

研究成果: Conference contribution

19 被引用数 (Scopus)

抄録

Social networks have recently garnered considerable interest. With the intention of utilizing social networks for the Semantic Web, several studies have examined automatic extraction of social networks. However, most methods have addressed extraction of the strength of relations. Our goal is extracting the underlying relations between entities that are embedded in social networks. To this end, we propose a method that automatically extracts labels that describe relations among entities. Fundamentally, the method clusters similar entity pairs according to their collective contexts in Web documents. The descriptive labels for relations are obtained from results of clustering. The proposed method is entirely unsupervised and is easily incorporated with existing social network extraction methods. Our experiments conducted on entities in researcher social networks and political social networks achieved clustering with high precision and recall. The results showed that our method is able to extract appropriate relation labels to represent relations among entities in the social networks.

本文言語English
ホスト出版物のタイトルIJCAI International Joint Conference on Artificial Intelligence
ページ2820-2825
ページ数6
出版ステータスPublished - 2007
外部発表はい
イベント20th International Joint Conference on Artificial Intelligence, IJCAI 2007 - Hyderabad, India
継続期間: 2007 1 62007 1 12

Other

Other20th International Joint Conference on Artificial Intelligence, IJCAI 2007
国/地域India
CityHyderabad
Period07/1/607/1/12

ASJC Scopus subject areas

  • 人工知能

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