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Performance Evaluation of Text Embedding Models for Ambiguity Classification in Indonesian News Corpus: A Comparative Study of TF-IDF, Word2Vec, FastText BERT, and GPT.

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Title: Performance Evaluation of Text Embedding Models for Ambiguity Classification in Indonesian News Corpus: A Comparative Study of TF-IDF, Word2Vec, FastText BERT, and GPT.
Authors: Sutriawan1,2 (AUTHOR) p41202200046@mhs.dinus.ac.id, Rustad, Supriadi3 (AUTHOR), Shidik, Guruh Fajar4 (AUTHOR), Pujiono1 (AUTHOR)
Source: Ingénierie des Systèmes d'Information. Jun2025, Vol. 30 Issue 6, p1469-1482. 14p.
Database: Business Source Ultimate
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  Data: <searchLink fieldCode="JN" term="%22Ingénierie+des+Systèmes+d'Information%22">Ingénierie des Systèmes d'Information</searchLink>. Jun2025, Vol. 30 Issue 6, p1469-1482. 14p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=bsu&AN=187416379
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        Value: 10.18280/isi.300606
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      – Code: eng
        Text: English
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      – TitleFull: Performance Evaluation of Text Embedding Models for Ambiguity Classification in Indonesian News Corpus: A Comparative Study of TF-IDF, Word2Vec, FastText BERT, and GPT.
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              Text: Jun2025
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              Y: 2025
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