Information-retrieval algorithm based on query expansion and classification
被引:0
作者:
Yue, Wen
论文数: 0引用数: 0
h-index: 0
机构:College of Computer and Communication, Hunan University, Changsha 410082, China
Yue, Wen
Chen, Zhi-Ping
论文数: 0引用数: 0
h-index: 0
机构:College of Computer and Communication, Hunan University, Changsha 410082, China
Chen, Zhi-Ping
Lin, Ya-Ping
论文数: 0引用数: 0
h-index: 0
机构:College of Computer and Communication, Hunan University, Changsha 410082, China
Lin, Ya-Ping
机构:
[1] College of Computer and Communication, Hunan University, Changsha 410082, China
[2] Software School, Hunan University, Changsha 410082, China
来源:
Xitong Fangzhen Xuebao / Journal of System Simulation
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2006年
/
18卷
/
07期
关键词:
D O I:
暂无
中图分类号:
学科分类号:
摘要:
A new information retrieval algorithm based on query expansion and classification was proposed. The algorithm is based on the observation that very short queries used in information searching often result in depressed precision and impressive recall. The approach is based on pseudo-feedback and text classification, and it attempts to catch more relevant documents for user. The results of the experiment show that the algorithm proposed improves more precision and efficiency than the traditional query expansion methods.