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Erschienen in:
2015 | OriginalPaper | Buchkapitel
Classifying Forum Questions Using PCA and Machine Learning for Improving Online CQA
verfasst von : Simon Fong, Yan Zhuang, Kexing Liu, Shu Zhou
Erschienen in: Soft Computing in Data Science
Verlag: Springer Singapore
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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.