Section Article

Constructing a systematic classification of knowledge derived from an internet-based educational platform for a university.
Author(s): R. P. Meena

Abstract
Electronic educational technology commonly referred to as e-learning portals is increasingly being used by educational institutions including schools colleges universities and individual instructors to create a learning environment by facilitating the exchange of information. Given the large amount of information that educational institutions accumulate it is crucial for them to streamline data administration and minimise data duplication. To achieve this objective the data architecture should provide a systematic methodology for the reuse and exchange of existing data. This study aims to automatically build a taxonomy from a given set of keywords in order to facilitate data sharing reuse and data search. The taxonomy generated should be autonomous from any other data classifications. The Bayesian Rose Tree and K-mean nearest neighbour classifier are two deployment approaches often used in taxonomy development. This is done to guarantee that increasing the number of distinct values would enhance the performance of the data mining model in terms of classification accuracy. The taxonomic approach and taxonomy may be used to real-world data to efficiently search for information.