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Query Expansion for Answer Document Retrieval in Chinese Question Answering System

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4 Author(s)
Zheng-Tao Yu ; The School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, 650051, P. R. China; Department of Computer Science & Engineering, Beijing Institute of Technology, Beijing, 100081, P. R. China; E-MAIL: ; Zhi-Yun Zheng ; Shi-Ping Tang ; Jian-Yi Guo

In document retrieval, query words expansion is normally based on semantic relation of query words. While using natural language questions to retrieve documents, because of more abundant semantic relation of question than that of query words, the precision can be improved by expanding query according to question characteristics. This paper puts forward a query expansion method for answering document retrieval in Chinese question answering system. The related words of question type are got through analyzing the question-answering pair, and the query are expanded with related words of question type. In order to verify the validity of query expansion method, a similarity computation method for question and document based on minimal match span is implemented. The word frequency and position information of query words and expansion words in the document are taken into consideration. The experiment results show that retrieval performance make substantial improvement using query expansion.

Published in:

2005 International Conference on Machine Learning and Cybernetics  (Volume:1 )

Date of Conference:

18-21 Aug. 2005