@inproceedings{5877d56c6f56444488af158723bbefb8,
title = "Multimodal DBN for predicting high-quality answers in cQA portals",
abstract = "In this paper, we address the problem for predicting cQA answer quality as a classification task. We propose a multimodal deep belief nets based approach that operates in two stages: First, the joint representation is learned by taking both textual and non-textual features into a deep learning network. Then, the joint representation learned by the network is used as input features for a linear classifier. Extensive experimental results conducted on two cQA datasets demonstrate the effectiveness of our proposed approach.",
author = "Haifeng Hu and Bingquan Liu and Baoxun Wang and Ming Liu and Xiaolong Wang",
year = "2013",
language = "英语",
isbn = "9781937284510",
series = "ACL 2013 - 51st Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference",
publisher = "Association for Computational Linguistics (ACL)",
pages = "843--847",
booktitle = "Short Papers",
address = "澳大利亚",
note = "51st Annual Meeting of the Association for Computational Linguistics, ACL 2013 ; Conference date: 04-08-2013 Through 09-08-2013",
}