Paper Title
Course Syllabus Comparison using Ontology Design and NLP

Abstract
Designing an ontology can be viewed as a knowledge management model in which data and information collected from various sources are transformed into knowledge for improvised reuse. Classes or concepts (entities) are grouped together systematically to create a taxonomic structure that forms the backbone of an ontology. This study aims to demonstrate the step-by-step development of a method to match and compare two or more ontologies of similar domains using NLP. The domain here focuses on subjects in the curriculum structure offered by various universities. This paper shows the automatic ontology matching and comparison process and gives a systematic evaluation of the relationships between features of matching ontologies. The subject chosen in this instance is software engineering and the ontology is designed according to the information provided by the particular university in its curriculum. Further, The paper discusses the use of python libraries like RDFLib, spaCy, NLTK and Count Vectorizer which plays an important role in parsing, processing, matching and comparison of ontologies. The automatic matching and comparison is made on the basis of lexical, structural and semantic similarity measures. Keywords - Knowledge Management, Ontology, Ontology Matching, Ontology Comparison, OWL, RDF, NLP, Feature Extraction.