A Method for Extracting Semantic Features from Sentences Based on a Fuzzy Logic Algorithm
Abstract
A Method for Extracting Semantic Features from Sentences Based on a Fuzzy Logic Algorithm
Incoming article date: 11.12.2025With the rapid growth of information on the internet, the accumulation of large databases, and the constant influx of data from various sensors and intelligent systems, it is becoming increasingly difficult for users to find what they are really looking for. Therefore, the development of automatic summarization methods is considered a crucial task in natural language processing. These needs have motivated the development of various methods and approaches for extracting semantic and semantic information from documents, classifying it, and systematizing it. This article develops the architecture of a hybrid-syntactic fuzzy system for extracting semantic features from text and presents its mathematical formalization. The author's method enables a transition from empirical assessments of word importance to a rigorous formalized calculation of their semantic weight.
Keywords: semantics, sentence, extraction, fuzzy logic, comparison, data