FISER: An effective method for detecting interactions between topic persons

Yung Chun Chang, Pi Hua Chuang, Chien Chin Chen, Wen Lian Hsu

研究成果: 書貢獻/報告類型會議貢獻

1 引文 斯高帕斯(Scopus)

摘要

Discovering the interactions between the persons mentioned in a set of topic documents can help readers construct the background of the topic and facilitate document comprehension. To discover person interactions, we need a detection method that can identify text segments containing information about the interactions. Information extraction algorithms then analyze the segments to extract interaction tuples and construct an interaction network of topic persons. In this paper, we define interaction detection as a classification problem. The proposed interaction detection method, called FISER, exploits nineteen features covering syntactic, context-dependent, and semantic information in text to detect interactive segments in topic documents. Empirical evaluations demonstrate the efficacy of FISER, and show that it significantly outperforms many well-known Open IE methods.
原文英語
主出版物標題Information Retrieval Technology - 8th Asia Information Retrieval Societies Conference, AIRS 2012, Proceedings
頁面275-285
頁數11
7675 LNCS
DOIs
出版狀態已發佈 - 2012
對外發佈
事件8th Asia Information Retrieval Societies Conference, AIRS 2012 - Tianjin, 中国
持續時間: 12月 17 201212月 19 2012

出版系列

名字Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
7675 LNCS
ISSN(列印)0302-9743
ISSN(電子)1611-3349

會議

會議8th Asia Information Retrieval Societies Conference, AIRS 2012
國家/地區中国
城市Tianjin
期間12/17/1212/19/12

ASJC Scopus subject areas

  • 電腦科學(全部)
  • 理論電腦科學

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