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Re-ranking method based on topic word pairs

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成果类型:
期刊论文
作者:
He, Tingting*何婷婷);Xu, Ting;Xu, Guozhong;Tu, Xinhui
通讯作者:
He, Tingting(何婷婷
作者机构:
[He, Tingting; Tu, Xinhui; Xu, Guozhong; Xu, Ting] Huazhong Normal Univ, Dept Comp Sci, Wuhan 430079, Hubei, Peoples R China.
[He, Tingting] Tsinghua Univ, Software Coll, Beijing 102201, Peoples R China.
通讯机构:
[He, Tingting] H
Huazhong Normal Univ, Dept Comp Sci, Wuhan 430079, Hubei, Peoples R China.
语种:
英文
期刊:
PACLIC 20 - Proceedings of the 20th Pacific Asia Conference on Language, Information and Computation
年:
2006
页码:
237-243
基金类别:
National Natural Science Foundation of China (NSFC) [60496323, 60375016, 10071028]; Ministry of education of China, Research Project for Science and technology [105117]
机构署名:
本校为第一且通讯机构
院系归属:
计算机学院
摘要:
How to improve the rankings of the relevant documents plays a key role in information retrieval. In this paper, a re-ranking approach based on topic words pair is proposed to improve precision while recall is preserved. The topic word pairs contain two correlated words, one of which is the original query word and the other come from the documents. The selection is based on Probabilistic Latent Semantic Indexing (PLSI). Then,the distribution of the Word pairs is used to re-rank documents. Results show a 53.6% and 56.8% improvement compare to the initial retrieval without any re-ranking, or quer...

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