VSM-RF: A Method of Relevance Feedback in Keyword Search over Relational Databases
(0) In Keyword Search Over Relational Databases (KSORD), retrieval of users initial query is often unsatisfying. User has to reformulate his query and execute the new query, which costs much time and effort. In this paper, a method of automatically reformulating user queries by relevance feedback is introduced, which is named VSM-RF. Aimed at the results of KSORD systems, VSM-RF adopts a ranking method based on vector space model to rank KSORD results. After the first time of retrieval, using user feedback or pseudo feedback just as user like, VSM-RF computes expansion terms based on probability and reformulates the new query using query expansion. After KSORD systems executing the new query, more relevant results are produced by the new query in the result list and presented to user. Experimental results verify this methods effectiveness.
PENG Zhao-hui ZHANG Jun WANG Shan WANG Chang-liang CUI Li-zhen
School of Computer Science and Technology, Shandong University, Jinan, 250101, China School of Computer Science and Technology, Dalian Maritime University, Dalian, 116026,China Key Labo Key Laboratory of Data Engineering and Knowledge Engineering, Ministry of Education,Beijing, 100872, The Hong Kong University of Science and Technology, Hong Kong, China
国际会议
2009 IEEE International Symposium on IT in Medicine & Education( IEEE 教育与医药信息化国际会议)
济南
英文
738-744
2009-08-14（万方平台首次上网日期，不代表论文的发表时间）