Abstract
A novel algorithm named the MTN (Multiple-Topic-Number) algorithm is introduced to deal with the problem of topic number selecting in topic model issue. The purpose of our algorithm is to build the LDA (Latent Dirichlet Allocation) matrices of different topic numbers to make the LDA matrices and machine learning algorithm combined better. So it can be used to solve the traditional problem of selecting topic number: under-size or over-size. The method here is to use different levels of machine learning tree structure to complete the combination. Experimental results show the efficiency of our proposed algorithm.
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Acknowledgement
This work was supported by Shenzhen Science and Technology Plan under grant number JCYJ20180306171938767 and the Shenzhen Foundational Research Funding JCYJ20180507183527919.
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Tang, L., Zhao, L. (2020). A Novel Topic Number Selecting Algorithm for Topic Model. In: Pan, JS., Lin, JW., Liang, Y., Chu, SC. (eds) Genetic and Evolutionary Computing. ICGEC 2019. Advances in Intelligent Systems and Computing, vol 1107. Springer, Singapore. https://doi.org/10.1007/978-981-15-3308-2_53
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DOI: https://doi.org/10.1007/978-981-15-3308-2_53
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