Stemming Algorithm

Stemming algorithms reduce words to their root forms, improving the efficiency of text processing tasks like keyword matching in information retrieval. Current research explores the application of large language models (LLMs) to enhance stemming accuracy, particularly by leveraging contextual information, while also refining rule-based and exemplar-based approaches for various languages. These advancements aim to improve the performance of natural language processing systems across diverse applications, including fake news detection and information retrieval, by addressing challenges like handling agglutinative languages and reducing errors in stemming.