Abstract
The Semantic Web aims to create a more intelligent web through the use of data that is understandable by machines, thus enabling the development of more powerful applications. In this context, ontology-based knowledge representation plays a crucial role in structuring and categorizing data in ways that enhance the effectiveness of data mining processes. This paper explores the concept of ontology-based knowledge representation in data mining, specifically in the Semantic Web, and its role in making data more interpretable, accessible, and usable. The paper examines various ontology models, knowledge representation frameworks, and how they interact with data mining techniques. It also highlights the importance of ontologies in ensuring consistency and semantic clarity, which is essential for the success of intelligent web-based applications. Additionally, the paper presents a set of use cases demonstrating the integration of ontology-based knowledge in data mining, followed by a discussion on the challenges and future directions for research in this area.
Keywords: Ontology, Knowledge Representation, Data Mining, Semantic Web, Semantic Technology, Intelligent Web, Ontology Models
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