Increasing Topic Coherence by Aggregating Topic Models

Author:

Blair Stuart J.,Bi Yaxin,Mulvenna Maurice D.

Publisher

Springer International Publishing

Reference21 articles.

1. Aletras, N., Stevenson, M.: Measuring the Similarity between automatically generated topics. In: Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics, pp. 22–27, Gothenburg (2014)

2. Blei, D.M., Griffiths, T.L., Jordan, M.I., Tenenbaum, J.B.: Hierarchical topic models and the nested Chinese restaurant process. Adv. Neural Inf. Process. Syst. 16, 17–24 (2004)

3. Blei, D.M., Ng, A., Jordan, M.I.: Latent Dirichlet allocation. J. Mach. Learn. Res. 3, 993–1022 (2003)

4. Chang, J., Gerrish, S., Wang, C., Boyd-Graber, J.L., Blei, D.M.: Reading tea leaves: how humans interpret topic models. In: Advances in Neural Information Processing Systems, pp. 288–296 (2009)

5. Deerwester, S., Dumais, S., Furnas, G., Landauer, T., Harshman, R.: Indexing by latent semantic analysis. J. Am. Soc. Inf. Sci. 41(6), 391–407 (1990)

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