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SIGIR
2002
ACM

Using self-supervised word segmentation in Chinese information retrieval

9 years 1 months ago
Using self-supervised word segmentation in Chinese information retrieval
We propose a self-supervised word-segmentation technique for Chinese information retrieval. This method combines the advantages of traditional dictionary based approaches with character based approaches, while overcoming many of their shortcomings. Experiments on TREC data show comparable performance to both the dictionary based and the character based approaches. However, our method is language independent and unsupervised, which provides a promising avenue for constructing accurate multilingual information retrieval systems that are flexible and adaptive. Categories and Subject Descriptors I.2 [Computing Methodologies]: artificial intelligence General Terms Experimentation Keywords Self-supervised word segmentation, Chinese IR
Fuchun Peng, Xiangji Huang, Dale Schuurmans, Nick
Added 23 Dec 2010
Updated 23 Dec 2010
Type Journal
Year 2002
Where SIGIR
Authors Fuchun Peng, Xiangji Huang, Dale Schuurmans, Nick Cercone, Stephen E. Robertson
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