Abstract
Topic detection in group chat has become a promising research due to the widely usage of Instant Messaging (IM) systems. Previous works mainly focus on improving the text similarity between two related messages by utilizing different weighting factors. However, the text similarity of related texts is likely to be zero (or near zero) due to the characteristics of short text messages in group chat. To solve this problem, an innovative topic detection method based on implicit reply which indicates chat messages interact with each other is proposed in this paper. The comparative experiments results on the datasets gathered from QQ groups demonstrate the superiority of the proposed method as compared to the baseline approaches.
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Acknowledgments
This work was supported by the Natural Science Foundation of China under Grant No.61070212 and 61572165, the State Key Program of Zhejiang Province Natural Science Foundation of China under Grant No. LZ15F020003.
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Zhang, X., Zheng, N., Xu, J., Xu, M. (2016). Topic Detection in Group Chat Based on Implicit Reply. In: Booth, R., Zhang, ML. (eds) PRICAI 2016: Trends in Artificial Intelligence. PRICAI 2016. Lecture Notes in Computer Science(), vol 9810. Springer, Cham. https://doi.org/10.1007/978-3-319-42911-3_56
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DOI: https://doi.org/10.1007/978-3-319-42911-3_56
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