Identification of Chinese event argument

Event extraction is a major task of Automatic Content Extraction (ACE) program. This paper focuses on the sub-task of event extraction, event argument identification, and proposes a novel method for Chinese event argument identification. The method involves two steps: (1) weighting features by the R...

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Bibliographic Details
Main Authors: Jian-feng Fu, Zong-tian Liu, Wei Liu
Format: Conference Proceeding
Language:English
Subjects:
Algorithm design and analysis
Clustering algorithms
Data mining
Electronic mail
Event detection
Machine learning
Natural languages
NIST
Pattern matching
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Summary:Event extraction is a major task of Automatic Content Extraction (ACE) program. This paper focuses on the sub-task of event extraction, event argument identification, and proposes a novel method for Chinese event argument identification. The method involves two steps: (1) weighting features by the ReliefF algorithm for considering the particular contributions of different features on clustering analysis, and (2) employing a semi-supervised clustering algorithm, Constrained-KMeans, to group event arguments. Compared with normal Constrained-KMeans algorithm, feature weighting obviously improves the F-Measure of identification. The comprehensive experimental results also demonstrate the outstanding performance of the new method.
DOI:10.1109/ICADIWT.2009.5273876