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Journal of Information Science and Engineering, Vol. 28 No. 1, pp. 51-65 (January 2012)

Semantic Link Analysis for Finding Answer Experts*

YAO LU1,2,3, XIAOJUN QUAN2, JINGSHENG LEI4, XINGLIANG NI1,2,3, WENYIN LIU2,3 AND YINLONG XU1,3
1School of Computer Science and Technology
University of Science and Technology of China
Hefei, 230026 P.R. China
2Department of Computer Science
City University of Hong Kong
HKSAR, P.R. China
3Joint Research Lab of Excellence
CityU-USTC Advanced Research Institute
Suzhou, 215123 P.R. China
4School of Computer and Information Engineering
Shanghai University of Electronic Power
Shanghai, 200090 P.R. China

Recommending unanswered questions to answer experts is an important mechanism in User-Interactive Question Answering (UIQA) services and is helpful to reduce asker's waiting time and obtain high-quality answers. In this paper, we address the task of identifying answer experts in UIQA services with semantic information extracted from user interaction behaviors. We first construct the user question-answer interaction graph through direct semantic links and latent links extracted from the records of question sessions and user profiles. After that, two expert-finding approaches are developed by employing the semantic information in the so-called propagation link analysis method and in the language model, respectively. Experimental results on Yahoo! Answers dataset show that the extracted semantic information indeed improves the performance of both propagation and language model for the task of answer experts finding.

Keywords: user-interactive question answering, answer expert finding, semantics, link analysis, language model

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Received February 14, 2011; revised August 9, 2011; accepted August 31, 2011.
Communicated by Irwin King.
* The work was supported by the Natural Science Foundation of China (No. 60863001, No. 61073038, No. 61073189) and Innovation Program of Shanghai Municipal Education Commission (No. 10ZZ115).