DMCA
Routing Questions for Collaborative Answering in Community Question Answering (2013)
| Citations: | 2 - 0 self |
BibTeX
@MISC{Chang13routingquestions,
author = {Shuo Chang and Aditya Pal},
title = {Routing Questions for Collaborative Answering in Community Question Answering},
year = {2013}
}
Share
 |
 |
 |
 |
||
OpenURL
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.
Keyphrases
community question answering collaborative answering question-answer thread large real-world dataset recommendation model similar query large volume abstract community question answering useful answer desirable expert several baseline model potential answerer compatible user empirical evidence valuable reference question asker prior work topical expertise
