Documents Ranking Based on a Hybrid Language Model for Chinese Information Retrieval

摘要：

For information retrieval, users hope to acquire more relevant information from the top N ranking documents. In this paper, a hybrid Chinese language model is presented, which is defined as a combination of ontology with statistical method, to improve the precision of top N ranking documents by reordering the initial retrieval documents. The experiment with NTCIR-3 formal Chinese test collection shows the proposed method improved the precision at top N ranking documents level.

关键词： Language model Documents ranking Linguistic Ontology knowledge Information retrieval

作者: Dequan Zheng Feng Yu Tiejun Zhao Sheng Li

作者单位: School of Computer and Information Engineering Harbin University of Commerce No.138, Tongda Street, School of Computer and Information Engineering Harbin University of Commerce No.138, Tongda Street, MOE-MS Key Laboratory of Natural Language Processing and Speech Harbin Institute of Technology No.92

会议类型: 国际会议

会议名称: 2006 IEEE International Conference on Information Acquisition

会议地点: 山东威海

会议语种:英文

页码: 279-283

在线出版日期: 2006-08-20（万方平台首次上网日期，不代表论文的发表时间）