A NOVEL APPROACH USING DATA MINING ON PREDICTING WALK-IN MALLS

The term Knowledge Discovery in Databases (KDD) refers to the broad process of finding knowledge in data, and emphasizes the high-level application of particular data mining methods. The unifying goal of the KDD process is to extract knowledge from data in the context of large databases. This article explores about the human foreboding (thoughts or feeling) and the tradition of shopping in a mall & how a shopping mall is a wonderful centre of entertainment nowadays. The research integrates and manipulates why people are into the shopping malls and the feasibility of the shopping malls into the decision tree model, for a transformation of Homo sapiens (modern humans belong) in shopping malls. This article uses a set of data for verification. Moreover, classification of data mining and predictive analysis is employed to mine the data. This research gives knowledge in a consumer's utilization based perspective about shopping in malls.