Topic Modeling of the SrpELTeC Corpus: A Comparison of NMF, LDA, and BERTopic

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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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-09-01
DOI
https://doi.org/10.5281/zenodo.13996169
Primary Topic
Computational and Text Analysis Methods
Type
article
Field-Weighted Citation Impact
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article

Topic Modeling of the SrpELTeC Corpus: A Comparison of NMF, LDA, and BERTopic

Zenodo (CERN European Organization for Nuclear Research)
Computational and Text Analysis Methods
article

Topic Modeling of the SrpELTeC Corpus: A Comparison of NMF, LDA, and BERTopic

article en

Abstract

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.

Zenodo (CERN European Organization for Nuclear Research)
University of Belgrade (RS), University of Belgrade – Faculty of Philology, University of Belgrade - Faculty of Mining and Geology
Quality Education
Openalex Percentile: Top 37%
Computational and Text Analysis Methods
DOIOpen Access PDFOpenAlex
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