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Department of Computer Science

Lin Gui

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Marie Curie Research Fellow

Room: 3.31
Email: Lin dot Gui at warwick dot ac dot uk

Introduction

I obtain my PhD degree from Harbin Institute of Technology, Shenzhen Graduate School, Shenzhen, China. My research interest includes Machine Learning, Nature Language Processing, and Sentiment Analysis. I am now a Marie Sklodowska-Curie Individual Fellow in University of Warwick, UK.

Select Publications

  • Lin Gui, Jia Leng, Gabriele Pergola, Yu Zhou, Ruifeng Xu, Yulan He. Neural Topic Model with Reinforcement Learning, Proceedings of Empirical Methods for Natural Language Processing (EMNLP) , 2019.
  • Lin Gui, Jiannan Hu, Yulan He, Qin Lu, Ruifeng Xu*, Jiachen Du. A Question Answering Approach to Emotion Cause Extraction, Proceedings of Empirical Methods for Natural Language Processing (EMNLP) , 2017.

  • Lin Gui, Ruifeng Xu*, Yulan He, Qin Lu and Zhongyu Wei. Intersubjectivity and Sentiment: from Language to Knowledge, in Proceedings of 25th International Joint Conference on Artificial Intelligence(IJCAI), pp.2789-2795, 2016.

  • Lin Gui† , Dongyin Wu†, Yu Zhou, Qin Lu and Ruifeng Xu*. Event-Driven Emotion Cause Extraction with Corpus Construction, in Proceedings of Empirical Methods for Natural Language Processing (EMNLP), pp.1639-1649, 2016. (†: equal contribution)
  • Lin Gui, Qin Lu*, Ruifeng Xu, Minglei Li, Qikang Wei. A Novel Class Noise Estimation Method and Application in Classification, In Proceedings of the 24th 24th ACM International Conference on Information and Knowledge Management (CIKM), pp.1081-1090, 2015.
  • Ruifeng Xu, Lin Gui, Jun Xu*, Qin Lu and Kam-Fai Wong. Cross Lingual Opinion Holder Extraction based on Multiple Kernel SVMs and Transfer Learning. World Wide Web, vol.18, no.2, pp.299-316, 2015.
  • Lin Gui, Ruifeng Xu*, Qin Lu, Jun Xu, Jian Xu, Bin Liu, Xiaolong Wang. Cross lingual Opinion Analysis via. Negative Transfer Detection, In Proceedings of the 52th Annual Meeting of the Association for Computational Linguistics (ACL), pp. 860-865, 2014.