Improving Knowledge Representation Using Knowledge Graphs: Tools and Techniques

Knowledge graphs have emerged as a powerful approach for representing and organizing vast amounts of data in a structured and interconnected manner. This research paper explores the construction of knowledge graphs, focusing on some of the techniques and methodologies involved. We have mentioned two approaches available among others for construction of the Knowledge Graph (KG). Here we investigate KG Construction utilizing available tools such as Apache Jena, Stardog, and others, as well as hands-on experience with Neo4j and other libraries such as AmpliGraph and SpaCy, also NetworkX Python. Furthermore, it discusses the challenges and future directions in knowledge graph construction. The insights provided in this paper aim to contribute to the understanding and advancement of knowledge graph construction methodologies and their application in various domains.