DocumentCode :
1823422
Title :
Routing questions for collaborative answering in Community Question Answering
Author :
Shuo Chang ; Pal, Arnab
Author_Institution :
Dept. of Comput. Sci., Univ. of Minnesota, Minneapolis, MN, USA
fYear :
2013
fDate :
25-28 Aug. 2013
Firstpage :
494
Lastpage :
501
Abstract :
Community Question Answering (CQA) service enables its users to exchange knowledge in the form of questions and answers. By allowing the users to contribute knowledge, CQA not only satisfies the question askers but also provides valuable references to other users with similar queries. Due to a large volume of questions, not all questions get fully answered. As a result, it can be useful to route a question to a potential answerer. In this paper, we present a question routing scheme which takes into account the answering, commenting and voting propensities of the users. Unlike prior work which focuses on routing a question to the most desirable expert, we focus on routing it to a group of users - who would be willing to collaborate and provide useful answers to that question. Through empirical evidence, we show that more answers and comments are desirable for improving the lasting value of a question-answer thread. As a result, our focus is on routing a question to a team of compatible users.We propose a recommendation model that takes into account the compatibility, topical expertise and availability of the users. Our experiments over a large real-world dataset shows the effectiveness of our approach over several baseline models.
Keywords :
Internet; collaborative filtering; question answering (information retrieval); CQA service; collaborative answering; collaborative effort; community question answering; compatibility; compatible users team; question routing scheme; question-answer thread; real-world dataset; topical expertise; user availability; Availability; Collaboration; Communities; Computational modeling; Java; Knowledge discovery; Routing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advances in Social Networks Analysis and Mining (ASONAM), 2013 IEEE/ACM International Conference on
Conference_Location :
Niagara Falls, ON
Type :
conf
Filename :
6785750
Link To Document :
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