Event mention detection using rough set and semantic similarity

Authors:
S. Sangeetha;Michael Arock;R. S. Thakur
Affiliations:
National Institute of Technology, Tiruchirappalli, Tamilnadu, India;National Institute of Technology, Tiruchirappalli, Tamilnadu, India;National Institute of Technology, Tiruchirappalli, Tamilnadu, India
Venue:
Proceedings of the 1st Amrita ACM-W Celebration on Women in Computing in India
Year:
2010

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Abstract

This paper proposes a method which correctly identifies the sentences that describe an event of interest to extract its participants. It uses rough set based on the attribute, number of sentences in which the term appears and semantic similarity between terms for pruning the terms further to form a list of event trigger. The proposed methodology then detects event mention from text documents using the list of event triggers. The significance of the proposed system is, it is the first system that applies rough set and semantic similarity for event mention identification. The entire work is divided into three tasks namely; natural language pre-processing, event trigger identification and event mention detection.