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    Ontology-based prompt tuning for news article summarization by A. R. S. Silva, Y. H. P. P. Priyadarshana

    Published 2025-02-01
    “…Ontology-based prompt tuning and abstractive text summarization techniques represent an advanced approach to enhancing the quality and contextual relevance of news article summaries. Despite the progress in natural language processing (NLP) and machine learning, existing methods often rely on extractive summarization, which lacks the ability to generate coherent and contextually rich summaries. …”
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    Types de chaînes de référence dans les articles de recherche de format IMRAD by Bruno Oberle

    Published 2019-12-01
    “…This dual typology of coreference chains allows us to describe the main types of chains, but also to give a fine-grained analysis of the textual progression in IMRAD articles, especially how and why some referents are present in several sections while others are limited to one section only.…”
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    Exploring the Effects of Pre-Processing Techniques on Topic Modeling of an Arabic News Article Data Set by Haya Alangari, Nahlah Algethami

    Published 2024-12-01
    “…Using the Single-label Arabic News Article Data set (SANAD), which includes 195,174 Arabic news articles, this study explores pre-processing methods such as cleaning, stemming, normalization, and stop word removal, which are crucial processes given the complex morphology of Arabic. …”
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    Collocations of high frequency words in nursing research articles and The Academic Collocation List: Similarities and differences by Mandić Kaja, Dankić Izabela

    Published 2020-12-01
    “…The focus is on noun-noun and noun-adjective collocations. The selected articles were converted into txt files using the ABBYY Fine Reader. …”
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    Collocations of high frequency words in nursing research articles and The Academic Collocation List: Similarities and differences by Kaja Mandić, Izabela Dankić

    Published 2025-01-01
    “…The focus is on noun-noun and noun-adjective collocations. The selected articles were converted into txt files using the ABBYY Fine Reader. …”
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    A Centrality-Weighted Bidirectional Encoder Representation from Transformers Model for Enhanced Sequence Labeling in Key Phrase Extraction from Scientific Texts by Tsitsi Zengeya, Jean Vincent Fonou Dombeu, Mandlenkosi Gwetu

    Published 2024-12-01
    “…Deep learning approaches, utilizing Bidirectional Encoder Representation from Transformers (BERT) and advanced fine-tuning techniques, have achieved state-of-the-art accuracies in the domain of term extraction from texts. …”
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    Corpus Development and NER Model for Identification of Legal Entities (Articles, Laws, and Sanctions) in Corruption Court Decisions in Indonesia by Edy Subowo, Imam Bukhori, warto

    Published 2025-06-01
    “…The NER model combines the IndoBERT (pre-trained language model) architecture with a CRF layer, fine-tuned to handle legal text complexities such as hierarchical article references (paragraphs, clauses) and amended laws citations (jo.). …”
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    Knitting Democracy, Separating Restraints: Legal Reform and a Critical Analysis of Article 256 of the New Criminal Code and its Impact on Freedom of Speech by Zico Junius Fernando, Kiki Kristanto, Ariesta Wibisono Anditya

    Published 2024-04-01
    “…In Indonesia's democratic landscape, the presence of Article 256 of the Criminal Code has become a crucial point in discussions on freedom of expression and human rights. …”
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