FORMAL METHODS FOR DETERMINING SEMANTIC SIMILARITY IN NATURAL LANGUAGE PROCESSING

Authors

  • Elmurod Zaylobidinovich Abdullayev

    Andijan State University image/svg+xml

Keywords: natural language processing, semantic similarity, formal methods, vector space model, algorithmic analysis

Abstract

This paper examines formal methods for measuring semantic similarity in natural language processing. It discusses the concept of semantic similarity using mathematical and algorithmic models, such as vector-space, probabilistic, and graph-based approaches. Formal criteria for evaluating semantic similarity are proposed, and their links to generalization ability and computational features are scientifically supported. The findings offer a foundational framework for assessing and enhancing NLP algorithms.

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