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All Journal Digital Zone: Jurnal Teknologi Informasi dan Komunikasi
Ansyah, Adi Surya Suwardi
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Computer Science & IT Engineering

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Integrated Named Entity Recognition and Identical-Entity Detection for Extracting Unique Information Sources in News Articles Ansyah, Adi Surya Suwardi; Oranova Siahaan, Daniel; izqi Paradisiaca , Brian R
Digital Zone: Jurnal Teknologi Informasi dan Komunikasi Vol. 16 No. 2 (2025): Digital Zone: Jurnal Teknologi Informasi dan Komunikasi
Publisher : Publisher: Fakultas Ilmu Komputer, Institution: Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/digitalzone.v16i2.27687

Abstract

Native advertising is often difficult to detect because it resembles regular news articles. One indicator is the absence of diverse information sources or the reliance on a single perspective. Therefore, it is necessary to employ an extraction technique capable of consolidating various forms of identical entity mentions. This study integrates an NER model based on XLNet+BiLSTM+CRF with identical entity classification using Levenshtein distance features and static and contextual vector representations. The results show an F1-score of 93.71% at the entity level and 92.84% for identical entity identification, along with a list of unique citation sources. These findings demonstrate that this unique list can be an additional feature in detecting native advertising, which often relies on a single source. With an average unique entity coverage of 97.40%, the proposed architecture can extract unique entities within news articles
Co-Authors Daniel Oranova Siahaan izqi Paradisiaca , Brian R