Relevance index for inferred knowledge in higher education domain using data mining

Abstract

Optimizing the real-life scenarios facilitate knowledge building. Developing a knowledge model for optimizing certain output criteria enhances the benefits by many folds. Even a non-profit sector like education needs to define knowledge models that optimize their functioning and eventually help in knowledge building. Quantifying the factors determining the academic well-being of the students in any educational organization is of prime importance. The paper exemplifies the implementation of Data Mining Technique to deduce knowledge through classification rules and further assign relevance index to inferred knowledge.