Journal of Data Mining and Knowledge Engineering ISSN: 3139-5341 (Online)

Abstract

The field of knowledge engineering has been significantly enhanced by the advent of predictive data mining algorithms. This paper investigates the application of various predictive models, such as decision trees, neural networks, and support vector machines, within knowledge engineering systems. Our research focuses on the implementation and optimization of these algorithms to improve knowledge discovery and extraction processes. By analyzing large datasets across different domains, we demonstrate the efficacy of predictive data mining in uncovering patterns and insights that are critical for strategic decision-making. The study provides a comprehensive overview of the methodologies and their impact on the evolution of knowledge engineering practices.

Keywords: Predictive Data Mining, Knowledge Engineering, Decision Trees, Neural Networks, Support Vector Machines