Abstract
As one of the most popular e-Business models, community question answering (CQA) services increasingly gather large amount of knowledge through the voluntary services of the online community across the globe. While most questions in CQA usually receive an answer posted by the peer users, it is found that the number of unanswered or ignored questions soared up high in the past few years. Understanding the factors that contribute to questions being answered as well as questions remain ignored can help the forum users to improve the quality of their questions and increase their chances of getting answers from the forum. In this study, feature selection method called Principal Component Analysis was used to extract the factors or components of the features. Then data mining techniques was used to identify the relevant features that will help predict the quality of questions.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Li, B., Jin, T., Lyu, M.R., King, I., Mak, B.: Analyzing and predicting question quality in community question answering services. In: Proceedings of the 21st International Conference Companion on World Wide Web, pp. 775–782. ACM, April 2012
Chen, L., Zhang, D., Mark, L.: Understanding user intent in community question answering. In: Proceedings of the 21st International Conference Companion on World Wide Web, pp. 823–828, April 2012
Anderson, A., Huttenlocher, D., Kleinberg, J., Leskovec, J.: Discovering value from community activity on focused question answering sites: a case study of stack overflow. In: Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 850–858 (2012)
Barua, A., Thomas, S.W., Hassan, A.E.: What are developers talking about? An analysis of topics and trends in stack overflow. Empirical Software Engineering, 1–36 (2012)
Mamykina, L., Manoim, B., Mittal, M., Hripcsak, G., Hartmann, B.: Design lessons from the fastest q&a site in the west. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 2857–2866, May 2011
Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Duchesnay, E.: Scikit-learn: Machine learning in Python. The Journal of Machine Learning Research 12, 2825–2830 (2011)
Ng, A.Y.: Feature selection, L 1 vs. L 2 regularization, and rotational invariance. In: Proceedings of the Twenty-First International Conference on Machine Learning. ACM, July 2004
Ratanamahatana, C.A., Gunopulos, D.: Scaling up the naive bayesian classifier: using decision trees for feature selection. In: Proc. Workshop Data Cleaning and Preprocessing (DCAP 2002), at IEEE Int’l Conf. Data Mining, ICDM 2002 (2002)
Weinberger, K., Blitzer, J., Saul, L.: Distance metric learning for large margin nearest neighbor classification. Advances in Neural Information Processing Systems 18, 1473 (2006)
Caruana, R., Niculescu-Mizil, A.: An empirical comparison of supervised learning algorithms. In: Proceedings of the 23rd International Conference on Machine Learning, pp. 161–168. ACM, June 2006
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer Science+Business Media Singapore
About this paper
Cite this paper
Fong, S., Zhuang, Y., Liu, K., Zhou, S. (2015). Classifying Forum Questions Using PCA and Machine Learning for Improving Online CQA. In: Berry, M., Mohamed, A., Yap, B. (eds) Soft Computing in Data Science. SCDS 2015. Communications in Computer and Information Science, vol 545. Springer, Singapore. https://doi.org/10.1007/978-981-287-936-3_2
Download citation
DOI: https://doi.org/10.1007/978-981-287-936-3_2
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-287-935-6
Online ISBN: 978-981-287-936-3
eBook Packages: Computer ScienceComputer Science (R0)