Work

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

Year: 2024

Type: article

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.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.13996168

Authors: Mihajlov, Teodora, Ikonić Nešić, Milica, Stanković, Ranka, Kitanović, Olivera

Institution: University of Belgrade

Language: English

Topic: Topic Modeling

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W6893088051

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