Abstract
In consideration of the features of microblog content such as short text, sparse feature words, and the huge scale, a hot topic detection method was suggested by this paper based on VSM and improved LDA hybrid model. This method first uses LDA model incorporating the PageRank algorithm, deeply mines the structure of the social network. Then the VSM model and the improved LDA model are used for hybrid modeling and to calculate the similarity of microblog. Finally, the hot topic clustering results are obtained through the single-pass clustering algorithm based on the hybrid model. The experimental results show that the proposed method can effectively improve the microblogging hot topic detection efficiency.
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Acknowledgements
This work is supported by the Nature Science Foundation of China (No. 61502281, 71772107).
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Liqing, Q., Haiyan, L., Xin, F., Wei, J. (2019). Hot Topic Detection Based on VSM and Improved LDA Hybrid Model. In: Pan, JS., Lin, JW., Sui, B., Tseng, SP. (eds) Genetic and Evolutionary Computing. ICGEC 2018. Advances in Intelligent Systems and Computing, vol 834. Springer, Singapore. https://doi.org/10.1007/978-981-13-5841-8_61
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DOI: https://doi.org/10.1007/978-981-13-5841-8_61
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