Topic Discovery in Massive Text Corpora Based on Min-Hashing

@article{FuentesPineda2019TopicDI,
  title={Topic Discovery in Massive Text Corpora Based on Min-Hashing},
  author={Gibran Fuentes-Pineda and Ivan Vladimir Meza Ruiz},
  journal={ArXiv},
  year={2019},
  volume={abs/1807.00938}
}
Abstract Topics have proved to be a valuable source of information for exploring, discovering, searching and representing the contents of text corpora. They have also been useful for different natural language processing tasks such as text classification, text summarization and machine translation. Most existing topic discovery approaches require the number of topics to be provided beforehand. However, an appropriate number of topics for a given corpus depends on its characteristics and is… Expand
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