BCTM: A Topic Modeling Method Based on External Information

Author:

Liu Gang,Wan Taiying,Yu Jinfeng,Zhan Kai,Wang Wei

Publisher

Springer Nature Switzerland

Reference19 articles.

1. Ye, J., Zou, B., Hong, Y., Shen, L., Zhu, Q., Zhou, G.: Negation and speculation scope detection in Chinese. J. Comput. Res. Dev. 56(7), 1506–1516 (2019). (in Chinese)

2. Blei, D.M., Ng, A.Y., Jordan, M.I.: Latent Dirichlet allocation. J. Mach. Learn. Res. 34(5), 993–1022 (2003)

3. Liu, Y., Wang, Z., Hou, Y., Yan, H.: A method of extracting malware features based on probabilistic topic model. J. Comput. Res. Dev. 56(11), 2339–3234 (2019). (in Chinese)

4. Lee, Y.Y., Ke, H., Yen, T.Y., et al.: Combining and learning word embedding with WordNet for semantic relatedness and similarity measurement. J. Am. Soc. Inf. Sci. 71(6), 657–670 (2020)

5. Limwattana, S., Prom-On, S.: Topic modeling enhancement using word embeddings. In: 2021 18th International Joint Conference on Computer Science and Software Engineering (JCSSE) (2021)

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