Reference

[1] The random forest, https://towardsdatascience.com/the-random-forest-algorithm-d457d499ffcd

[2] Classification and Rating Administration, https://filmratings.com/content/downloads/rating_rules.pdf

[3] Commission Seeks Comment on Revised Industry Proposal for Rating Video Programming (CS Docket No. 97-55), https://transition.fcc.gov/Bureaus/Cable/Public_Notices/1997/fcc97321.html

[4] Topic Modeling and Latent Dirichlet Allocation (LDA) in Python, https://towardsdatascience.com/topic-modeling-and-latent-dirichlet-allocation-in-python-9bf156893c24

[5] LDA topic model, https://blog.csdn.net/aws3217150/article/details/53840029

[6] DIY word2vec, https://blog.csdn.net/u014595019/article/details/51884529

[7] models.word2vec – Word2vec embeddings, https://radimrehurek.com/gensim/models/word2vec.html

[8] jieba, https://github.com/fxsjy/jieba

[9] TextRank: Bringing Order into Texts, https://web.eecs.umich.edu/~mihalcea/papers/mihalcea.emnlp04.pdf

[10] Online classifiers for Chinese text classification and filtering, https://ieeexplore.ieee.org/document/1275988

[11] Design of Chinese Text Categorization Classifier Based on Attribute Bagging, https://ieeexplore.ieee.org/document/5208903

[12] Study on an Improved Naive Bayesian Classifier Used in the Chinese Text Categorization, https://ieeexplore.ieee.org/document/5558293

[13] Non-Independent term selection for Chinese text categorization, https://ieeexplore.ieee.org/document/6073168

[14] Deep feature weighting in Naive Bayes for Chinese text classification, https://ieeexplore.ieee.org/document/7790245