November 9, 2025Journal of Intelligent & Fuzzy Systems

Approaches, Tools, Algorithms, and Methods for Automatic Term Extraction: A Systematic Literature Mapping

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Findings reveal that hybrid approaches dominate automatic term extraction strategies, showing a 50% preference in the literature.
Analysis of 113 publications between 2015 and 2022 identifies algorithms like C-Value and TF-IDF as key contributors, with NLTK as the preferred tool.
Assessment utilizes systematic literature mapping, revealing significant trends and gaps in the domain of automatic term extraction.
Research indicates a crucial need for formal development methodologies in automatic term extraction for broader application across NLP domains.

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Implication

Systematic literature mapping uncovers trends in automatic term extraction, highlighting algorithms and tools like NLTK for enhanced NLP applications.

Cite This Study

Andrade et al. (2025) studied this question.

synapsesocial.com/papers/690fdce2f60c54d04ea3848b https://doi.org/10.1177/18758967251392652

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Implication

Systematic literature mapping uncovers trends in automatic term extraction, highlighting algorithms and tools like NLTK for enhanced NLP applications.

Approaches, Tools, Algorithms, and Methods for Automatic Term Extraction: A Systematic Literature Mapping

Key Points

Discussion

Implication

Cite This Study

Approaches, Tools, Algorithms, and Methods for Automatic Term Extraction: A Systematic Literature Mapping

Key Points

Discussion

Implication

Cite This Study

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