Journal
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
Volume 29, Issue 8, Pages 1723-1736Publisher
IEEE COMPUTER SOC
DOI: 10.1109/TKDE.2017.2696535
Keywords
Question answering; voting prediction; non-linearity; coupling; dynamics
Categories
Funding
- National Key Research and Development Program of China [2016YFB1000802]
- National 863 Program of China [2015AA01A203]
- National Natural Science Foundation of China [61672274, 61690204]
- Collaborative Innovation Center of Novel Software Technology and Industrialization
- NSF [IIS-1651203]
- DTRA [HDTRA1-16-0017]
- ARO [W911NF-16-1-0168]
- NIH [R01LM011986]
- RUTC2 [49997-33 25]
- Baidu gift
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Community Question Answering (CQA) sites, such as Stack Overflow and Yahoo! Answers, have become very popular in recent years. These sites contain rich crowdsourcing knowledge contributed by the site users in the form of questions and answers, and these questions and answers can satisfy the information needs of more users. In this article, we aim at predicting the voting scores of questions/answers shortly after they are posted in the CQA sites. To accomplish this task, we identify three key aspects that matter with the voting of a post, i.e., the non-linear relationships between features and output, the question and answer coupling, and the dynamic fashion of data arrivals. A family of algorithms are proposed to model the above three key aspects. Some approximations and extensions are also proposed to scale up the computation. We analyze the proposed algorithms in terms of optimality, correctness, and complexity. Extensive experimental evaluations conducted on two real data sets demonstrate the effectiveness and efficiency of our algorithms.
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