TESLA - Text Embeddings - Serbian Language Applications
Published September 2024 | Version v1
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Topic Modeling of the SrpELTeC Corpus: A Comparison of NMF, LDA, and BERTopic

Authors/Creators

  • 1. ROR icon University of Belgrade
  • 2. ROR icon University of Belgrade – Faculty of Philology
  • 3. ROR icon University of Belgrade - Faculty of Mining and Geology

Description

At the "19th Conference on Computer Science and Intelligence Systems, FedCSIS 2024 (IEEE #61123)" held in Belgrade, September 8–11, 2024, a paper titled Topic Modeling of the SrpELTeC Corpus: A Comparison of NMF, LDA, and BERTopic, autora Teodora Mihajlov, Milica Ikonić Nešić, Ranka Stanković and Olivera Kitanović, was presented within the session Challenges for Natural Language Processing (CNLPS), showcasing the results of the TESLA project.

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FedCSIS2024_Topic-Modeling.pdf

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