Abstract
Sentiment target extraction on Chinese microblog has attracted increasing research attention. Most previous work relies on syntax, such as automatic parse trees, which are subject to noise for informal text such as microblog. In this paper, we propose a modified CRFs model for Chinese microblog sentiment target extraction. This model see the sentiment target extraction as a sequence-labeling problem, incorporating the contextual information, syntactic rules and opinion lexicon into the model with multi-features. The major contribution of this method is that it can be applied to the texts in which the targets are not mentioned in the sequence. Experimental results on benchmark datasets show that our method can consistently outperform the state-of-the-art methods.
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Acknowledgments
This work is financially supported by NSFC-Guangdong Joint Found (U1501254), Natural Science Foundation of China (61202269, 61472089, 61572143, 61502108, 61502109), Natural Science Foundation of Guangdong province (2014A030306004, 2014A030308008), Key Technology Research and Development Programs of Guangdong Province (2012B01010029, 2013B051000076, 2015B010108006, 2015B010131015), Science and Technology Plan Project of Guangzhou City (2014Y2-00027), Opening Project of the State Key Laboratory for Novel Software Technology (KFKT2014B03, KFKT2014B23), Philosophy and social science project of Guangdong Provenience (GD14XYJ24), Young innovative talents project of Guangdong Province (2015KQNCX027), The experimental teaching reform project of Guangdong university of technology (2015SY45).
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Chen, B., Hao, Z., Cai, R., Wen, W., Du, S. (2016). Sentiment Target Extraction Based on CRFs with Multi-features for Chinese Microblog. In: Morishima, A., et al. Web Technologies and Applications. APWeb 2016. Lecture Notes in Computer Science(), vol 9865. Springer, Cham. https://doi.org/10.1007/978-3-319-45835-9_3
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DOI: https://doi.org/10.1007/978-3-319-45835-9_3
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