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http://dx.doi.org/10.3745/KIPSTB.2010.17B.5.399

A Method for Precision Improvement Based on Core Query Clusters and Term Proximity  

Jang, Kye-Hun (전북대학교 컴퓨터공학과)
Lee, Kyung-Soon (전북대학교 컴퓨터공학부/영상정보신기술연구센터)
Publication Information
The KIPS Transactions:PartB / v.17B, no.5, 2010 , pp. 399-404 More about this Journal
Abstract
In this paper, we propose a method for precision improvement based on core clusters and term proximity. The method is composed by three steps. The initial retrieval documents are clustered based on query term combination, which occurred in the document. Core clusters are selected by using proximity between query terms. Then, the documents in core clusters are reranked based on context information of query. On TREC AP test collection, experimental results in precision at the top documents(P@100) show that the proposed method improved 11.2% over the language model.
Keywords
Query Term Cluster; Core Query; Term Proximity; Context Term; Reranking;
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Times Cited By KSCI : 1  (Citation Analysis)
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