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ACL
2009

Query Segmentation Based on Eigenspace Similarity

10 years 4 months ago
Query Segmentation Based on Eigenspace Similarity
Query segmentation is essential to query processing. It aims to tokenize query words into several semantic segments and help the search engine to improve the precision of retrieval. In this paper, we present a novel unsupervised learning approach to query segmentation based on principal eigenspace similarity of queryword-frequency matrix derived from web statistics. Experimental results show that our approach could achieve superior performance of 35.8% and 17.7% in Fmeasure over the two baselines respectively, i.e. MI (Mutual Information) approach and EM optimization approach.
Chao Zhang, Nan Sun, Xia Hu, Tingzhu Huang, Tat-Se
Added 16 Feb 2011
Updated 16 Feb 2011
Type Journal
Year 2009
Where ACL
Authors Chao Zhang, Nan Sun, Xia Hu, Tingzhu Huang, Tat-Seng Chua
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