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A Study on Mapping Users` Topic Interest for Question Routing for Community-based Q&A Service
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 Title & Authors
A Study on Mapping Users` Topic Interest for Question Routing for Community-based Q&A Service
Park, Jong Do;
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The main goal of this study is to investigate how to route a question to some relevant users who have interest in the topic of the question based on users` topic interest. In order to assess users` topic interest, archived question-answer pairs in the community were used to identify latent topics in the chosen categories using LDA. Then, these topic models were used to identify users` topic interest. Furthermore, the topics of newly submitted questions were analyzed using the topic models in order to recommend relevant answerers to the question. This study introduces the process of topic modeling to investigate relevant users based on their topic interest.
community-based Q&A;social Q&A;question routing;question triage;topic model;LDA (Latent Dirichlet Allocation);
 Cited by
사용자 리뷰를 통한 소셜커머스와 오픈마켓의 이용경험 비교분석,채승훈;임재익;강주영;

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Adamic, L. A., Zhang, J., Bakshy, E., & Ackerman, M. S. (2008, April). Knowledge sharing and yahoo answers: everyone knows something. In Proceedings of the 17th international conference on World Wide Web (pp. 665-674). ACM.

Agichtein, E., Castillo, C., Donato, D., Gionis, A., & Mishne, G. (2008, February). Finding high-quality content in social media. In Proceedings of the 2008 International Conference on Web Search and Data Mining (pp. 183-194). ACM.

Bouguessa, M., Dumoulin, B., & Wang, S. (2008, August). Identifying authoritative actors in question-answering forums: the case of yahoo! answers. In Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining (pp. 866-874). ACM.

Chang, S., & Pal, A. (2013, August). Routing questions for collaborative answering in community question answering. In Advances in Social Networks Analysis and Mining (ASONAM), 2013 IEEE/ACM International Conference on (pp. 494-501). IEEE.

Farzan, R., & Brusilovsky, P. (2011). Encouraging user participation in a course recommender system: An impact on user behavior. Computers in Human Behavior, 27(1), 276-284. crossref(new window)

Jeon, J., Croft, W. B., & Lee, J. H. (2005, October). Finding similar questions in large question and answer archives. In Proceedings of the 14th ACM international conference on Information and knowledge management (pp. 84-90). ACM.

Jurczyk, P., & Agichtein, E. (2007). Discovering authorities in question answer communities by using link analysis. Paper presented at the Proceedings of the sixteenth ACM conference on Conference on information and knowledge management.

Kim, Soojung (2012). Research Trends of the Credibility of Information in Social Q&A. Journal of the Korean Society for Information Management, 29(2), 135-154.

Liu, M., Liu, Y., & Yang, Q. (2010). Predicting best answerers for new questions in community question answering. In Web-Age Information Management (pp. 127-138). Springer Berlin Heidelberg.

Ng, A. Y., Jordan, M. I., & Weiss, Y. (2002). On spectral clustering: Analysis and an algorithm. Advances in neural information processing systems, 2, 849-856.

Oh, S. (2010). Answerers' Motivations and Strategies for Providing Information and Social Support in Social Q&A an Investigation of Health Question Answering. ProQuest LLC. 789 East Eisenhower Parkway, PO Box 1346, Ann Arbor, MI 48106.

Qu, M., Qiu, G., He, X., Zhang, C., Wu, H., Bu, J., & Chen, C. (2009, April). Probabilistic question recommendation for question answering communities. In Proceedings of the 18th international conference on World wide web (pp. 1229-1230). ACM.

Shah, C. (2011). Measuring effectiveness and user satisfaction in Yahoo! Answers. First Monday, 16(2).

Zhang, J., Tang, J., & Li, J. (2007). Expert finding in a social network. In Advances in Databases: Concepts, Systems and Applications (pp. 1066-1069). Springer Berlin Heidelberg.