COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Chinese Word Segmentation and Named Entity Recognition: A Pragmatic Approach
Computational Linguistics
SIGHAN '03 Proceedings of the second SIGHAN workshop on Chinese language processing - Volume 17
A search-based Chinese word segmentation method
Proceedings of the 16th international conference on World Wide Web
Translation disambiguation in web-based translation extraction for English-Chinese CLIR
Proceedings of the 2007 ACM symposium on Applied computing
GPX: gardens point XML IR at INEX 2005
INEX'05 Proceedings of the 4th international conference on Initiative for the Evaluation of XML Retrieval
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A distinctive feature of Chinese test is that a Chinese document is a sequence of Chinese with no space or boundary between Chinese words. This feature makes Chinese information retrieval more difficult since a retrieved document which contains the query term as a sequence of Chinese characters may not be really relevant to the query since the query term (as a sequence Chinese characters) may not be a valid Chinese word in that documents. On the other hand, a document that is actually relevant may not be retrieved because it does not contain the query sequence but contains other relevant words. In this research, we propose a hybrid Chinese information retrieval model by incorporating word-based techniques with the traditional character-based techniques. The aim of this approach is to investigate the influence of Chinese segmentation on the performance of Chinese information retrieval. Two ranking methods are proposed to rank retrieved documents based on the relevancy to the query calculated by combining character-based ranking and word-based ranking. Our experimental results show that Chinese segmentation can improve the performance of Chinese information retrieval, but the improvement is not significant if it incorporates only Chinese segmentation with the traditional character-based approach.