Development of a Best Answer Recommendation Model in a Community Question Answering (CQA) System
- 1 Department of Information and Communication Technology, Adekunle Ajasin University, Akungba-Akoko, Nigeria
- 2 Department of Computer Science, Federal University of Technology, Akure, Nigeria
- 3 Department of Information Systems, Federal University of Technology, Akure, Nigeria
- 4 Department of Information Technology, Federal University of Technology, Akure, Nigeria
- 5 Department of Computer Science, Federal University of Technology, Akure, Nigeria
Abstract
In this work, a best answer recommendation model is proposed for a Question Answering (QA) system. A Community Question Answering System was subsequently developed based on the model. The system applies Brouwer Fixed Point Theorem to prove the existence of the desired voter scoring function and Normalized Google Distance (NGD) to show closeness between words before an answer is suggested to users. Answers are ranked according to their Fixed-Point Score (FPS) for each question. Thereafter, the highest scored answer is chosen as the FPS Best Answer (BA). For each question asked by user, the system applies NGD to check if similar or related questions with the best answer had been asked and stored in the database. When similar or related questions with the best answer are not found in the database, Brouwer Fixed point is used to calculate the best answer from the pool of answers on a question then the best answer is stored in the NGD data-table for recommendation purpose. The system was implemented using PHP scripting language, MySQL for database management, JQuery, and Apache. The system was evaluated using standard metrics: Reciprocal Rank, Mean Reciprocal Rank (MRR) and Discounted Cumulative Gain (DCG). The system eliminated longer waiting time faced by askers in a community question answering system. The developed system can be used for research and learning purposes.
- Anietie, A., Satoshi, S., Mugizi, R. and Mark, D. (2016) Name Variation in Community Question Answering Systems. In Proceedings of the 2nd Workshop on Noisy User-generated Text, Osaka, Japan, 12 December 2016, 51-60.
- Liu, Y.J., Li, S.S., Cao, Y.B., Lin, C.Y., Han, D.Y. and Yu, Y.J. (2008) Understanding and Summarizing Answers in Community-Based Question Answering Services. In Proceedings of the 22nd International Conference on Computational Linguistics (COLING), Manchester, UK, 18-22 August 2008, 497-504.
- Agichtein, E., Castillo, C., Donato, D., Gionis, A. and Mishne, G. (2008) Finding High-Quality Content in Social Media. Proceedings of the 2008 International Conference on Web Search and Data Mining, Phoenix, February 2008, 183-194. https://doi.org/10.1145/1341531.1341557
- Maria, S.P. and Yin-kai, N. (2011) A Community Question-Answering Refinement System. Proceedings of the 22nd ACM Conference on Hypertext and Hypermedia, Eindhoven, The Netherlands, 6-9 June 2011.
- Chen, L. (2014) Understanding and Exploiting User Intent in Community Question Answering. Ph.D. Dissertation, Birkbeck University of London, London. https://doi.org/10.1007/978-3-642-45068-6_34
- Antoaneta, B. and Grzegorz, C. (2015) Question Quality in Community Question Answering Forums: A Survey. SIGKDD Explorations, 17, 8-13.
- Stack Overflow. https://stackoverflow.com/
- Liangjie, H. and Davison, B.D. (2009) A Classification-Based Approach to Question Answering in Discussion Boards. Proceedings of the 32nd Annual Int’l ACM SIGIR Conferences on Research and Development in Information Retrieval, Boston, July 2009, 171-178.
- Kleinberg, J.M. (1999) Authoritative Sources in a Hyperlinked Environment. Journal of the ACM, 46, 604-632. https://doi.org/10.1145/324133.324140
- Page, L., Brin, S., Motwani, R. and Winograd, T. (1999) The Page Rank Citation Ranking: Bringing Order to the Web. Stanford Info Lab, Technical Report 1999-66, November 1999.
- Michael, H. and Noah, S. (2010) Good Question! Statistical Ranking for Question Generation. Proceedings of Human Language Technologies Conference of the North American Chapter of the Association of Computational Linguistics, Los Angeles, California, USA, 2-4 June 2010, 609-617.
- Shuo, C. and Aditya, P. (2013) Routing Questions for Collaborative Answering in Community Question Answering. ASONAM 13 Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, Ontario, August 2013, 494-501.