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ACL
2006

Unsupervised Relation Disambiguation Using Spectral Clustering

11 years 9 months ago
Unsupervised Relation Disambiguation Using Spectral Clustering
This paper presents an unsupervised learning approach to disambiguate various relations between name entities by use of various lexical and syntactic features from the contexts. It works by calculating eigenvectors of an adjacency graph's Laplacian to recover a submanifold of data from a high dimensionality space and then performing cluster number estimation on the eigenvectors. Experiment results on ACE corpora show that this spectral clustering based approach outperforms the other clustering methods.
Jinxiu Chen, Dong-Hong Ji, Chew Lim Tan, Zheng-Yu
Added 30 Oct 2010
Updated 30 Oct 2010
Type Conference
Year 2006
Where ACL
Authors Jinxiu Chen, Dong-Hong Ji, Chew Lim Tan, Zheng-Yu Niu
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