@inproceedings{8c14f99c73b845fd88d5cf4f7fe8c74d,
title = "A novel topic number selecting algorithm for topic model",
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.",
keywords = "LDA, Topic model, Xgboost",
author = "Linlin Tang and Liang Zhao",
note = "Publisher Copyright: {\textcopyright} Springer Nature Singapore Pte Ltd. 2020.; 13th International Conference on Genetic and Evolutionary Computing, ICGEC 2019 ; Conference date: 01-11-2019 Through 03-11-2019",
year = "2020",
doi = "10.1007/978-981-15-3308-2\_53",
language = "英语",
isbn = "9789811533075",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer",
pages = "483--490",
editor = "Jeng-Shyang Pan and Yongquan Liang and Lin, \{Jerry Chun-Wei\} and Shu-Chuan Chu",
booktitle = "Genetic and Evolutionary Computing - Proceedings of the 13th International Conference on Genetic and Evolutionary Computing, 2019",
address = "德国",
}