Topic Modeling on Podcast Short-Text Metadata

Author:

Valero Francisco B.ORCID,Baranes MarionORCID,Epure Elena V.ORCID

Publisher

Springer International Publishing

Reference38 articles.

1. Akbik, A., Blythe, D., Vollgraf, R.: Contextual string embeddings for sequence labeling. In: COLING 2018, 27th International Conference on Computational Linguistics, pp. 1638–1649 (2018)

2. Benton, G., Fazelnia, G., Wang, A., Carterette, B.: Trajectory based podcast recommendation. arXiv preprint arXiv:2009.03859 (2020)

3. Besser, J., Larson, M., Hofmann, K.: Podcast search: user goals and retrieval technologies. Online Inf. Rev. 43(3), 395–419 (2010). https://doi.org/10.1108/14684521011054053

4. Bianchi, F., Terragni, S., Hovy, D.: Pre-training is a hot topic: contextualized document embeddings improve topic coherence. In: Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2: Short Papers), pp. 759–766. Association for Computational Linguistics, August 2021. https://doi.org/10.18653/v1/2021.acl-short.96. https://aclanthology.org/2021.acl-short.96

5. Bird, S., Klein, E., Loper, E.: Natural Language Processing with Python: Analyzing Text with the Natural Language Toolkit. O’Reilly Media, Inc., Sebastopol (2009)

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