Authors : Ritesh Verma; Bhumi Bhoi

Volume/Issue : Volume 9 - 2024, Issue 5 - May

Google Scholar : https://tinyurl.com/bdcn5pv3

Scribd : https://tinyurl.com/bdcrecc6

DOI : https://doi.org/10.38124/ijisrt/IJISRT24MAY1721

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : The convergence of rules, ontology, and natural language processing (NLP) represents a pivotal domain in the realm of textual data analysis and interpretation. This comprehensive study delves into the intricate interplay among these three pillars of information processing, aiming to elucidate their collective impact on advancing our understanding and manipulation of textual data. Through a meticulous examination of the theoretical underpinnings and practical applications of rules, ontology, and NLP, we endeavor to uncover novel insights and methodologies for enhancing automated textual analysis and interpretation. By exploring the intersection of these disciplines, we seek to unravel the complexities inherent in textual data and pave the way for new horizons in information extraction and knowledge discovery. Join us on this journey as we navigate the fascinating landscape of rules, ontology, and NLP, and unravel their profound implications for the field of textual data analysis.

Keywords : Leveraging Machine Learning and NLP.

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