Title :
Documents Ranking Based on a Hybrid Language Model for Chinese Information Retrieval
Author :
Zheng, Dequan ; Yu, Feng ; Zhao, Tiejun ; Li, Sheng
Author_Institution :
Sch. of Comput. & Inf. Eng., Harbin Univ. of Commerce
Abstract :
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
Keywords :
document handling; information retrieval; natural languages; ontologies (artificial intelligence); statistical analysis; Chinese information retrieval; N ranking documents; hybrid language model; ontology; statistical method; Business; Indexing; Information retrieval; Laboratories; Natural languages; Ontologies; Semantic Web; Speech processing; Statistical analysis; Testing; Documents ranking; Information retrieval; Language model; Linguistic Ontology knowledge;
Conference_Titel :
Information Acquisition, 2006 IEEE International Conference on
Conference_Location :
Weihai
Print_ISBN :
1-4244-0528-9
Electronic_ISBN :
1-4244-0529-7
DOI :
10.1109/ICIA.2006.306010
