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Prof. Qing Li and his research team won the Best Research Paper Award at WI-IAT’20

17 Dec 2020


Congratulations to Prof. Qing Li, Chair Professor of Data Science and Head of COMP, and his research team on receiving the Best Research Paper Award at the 2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT '20) with the paper titled “EmoChannelAttn: Exploring Emotional Construction Towards Multi-Class Emotion Classification”.

The current multi-class emotion classification studies mainly focus on enhancing word-level and sentence-level semantical and sentimental features by exploiting hand-crafted lexicon dictionaries. In comparison, very limited studies attempt to achieve emotion classification task from the emotion-level perspectives, which are to understand how the emotion of a sentence is constructed. Another limitation of existing works is that people assumed that emotion labels are relatively independent, neglecting the possible relations among different types of emotions.

In this paper, the team aims at exploring various fine-grained emotions based on domain knowledge to understand the construction details of emotions and the interconnection among emotions. To address the first issue, the team proposes a novel method named EmoChannel to capture the intensity variation of a particular emotion in time series by incorporating domain knowledge and dimensional sentiment lexicons. The resulting information of 151 available fine-grained emotions is utilised to comprise the sentence-level emotion construction. As for the second issue, the EmoChannelAttn Network is introduced to identify the dependency relationship within all emotions via attention mechanism to enhance emotion classification performance. The experiments demonstrate that the proposed method gains significant improvements compared with baseline models on several multi-class datasets.

WI-IAT provides a premier forum and features high-quality, original research papers and real-world applications in all theoretical and technology areas that make up the field of Web Intelligence and Intelligent Agent Technology.


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