Context-Aware Latent Dirichlet Allocation for Topic Segmentation-Reference-Cited by-同舟云学术

Context-Aware Latent Dirichlet Allocation for Topic Segmentation

Published:2020 Issue: Volume: Page:475-486
ISSN:0302-9743
Container-title:Advances in Knowledge Discovery and Data Mining
language:
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Author:

Li Wenbo,Matsukawa Tetsu,Saigo Hiroto,Suzuki Einoshin

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-47426-3_37

Reference27 articles.

1. Amoualian, H., Lu, W., Gaussier, M.: Topical coherence in LDA-based models through induced segmentation. In: Proceedings of ACL, vol. 1, pp. 1799–1809 (2017)

2. Balikas, G., Amoualian, H., Clausel, M., Gaussier, E., Amini, M.R.: Modeling topic dependencies in semantically coherent text spans with copulas. In: Proceedings of COLING, pp. 1767–1776 (2016)

3. Beeferman, D., Berger, A., Lafferty, J.: Statistical models for text segmentation. Mach. Learn. 34(1–3), 177–210 (1999)

4. Blei, D.M., Moreno, P.J.: Topic segmentation with an aspect hidden Markov model. In: Proceedings of SIGIR, pp. 343–348 (2001)

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

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