VARIANCE ROVER SYSTEM: WEB ANALYTICS TOOL USING DATA MINING

G. S. Kalekar, A.P.Mulmule, A. A. Pujari, A. A. Ugaonkar

Abstract: Learning Analytics by nature relies on computational information processing activities intended to extract from raw data some interesting aspects that can be used to obtain insights into the behaviors of learners, the design of learning experiences, etc. There is a large variety of computational techniques that can be employed, all with interesting properties, but it is the interpretation of their results that really forms the core of the analytics process. As a rising subject, data mining and business intelligence are playing an increasingly important role in the decision support activity of every walk of life. The Variance Rover System (VRS) mainly focused on the large data sets obtained from online web visiting and categorizing this into clusters according some similarity and the process of predicting customer behavior and selecting actions to influence that behavior to benefit the company, so as to take optimized and beneficial decisions of business expansion.

Keywords: Analytics, Business intelligence, Clustering, Data Mining, Standard K-means, Optimized K-means

DOI: https://doi.org/10.15623/ijret.2014.0301060