Review of Natural Language Semantics a Deep Dive into Probabilistic and Fuzzy Logic Approaches

Abstract

Semantics has long been the primary focus of Natural Language Processing (NLP) researchers and practitioners, who strive to analyse and develop new forms of human speech. This book offers a thorough overview of the probabilistic and fuzzy logic techniques, two of the most significant approaches in the field of natural language semantics. Both techniques have evolved into indispensable instruments for comprehending the complexity of the human language. Probabilistic semantics utilises the strengths of statistics and probability in order to help robots predict and comprehend verbal structures based on historical evidence. By incorporating degrees of truth rather than binary true or false structures, fuzzy logic semantics enters the world of uncertainty and imprecision. This more closely resembles the capacity of humans to grasp confusing and imprecise statements. In this study, we compare and contrast the two approaches, highlighting their distinctions and illuminating the situations in which each is most beneficial. In addition, we illustrate real-world applications and case studies in which these ideas have been successfully implemented, so shedding light on their practical implications and potential future developments. This review aims to inspire continued research and development of probabilistic and fuzzy logic semantic techniques in natural language processing by providing researchers, linguists, and engineers with a comprehensive understanding of these techniques.