Published Paper Details:

Data Mining [1, 2] or knowledge discovery is a method of extracting interesting, non-trivial, implicit, previously unknown and potentially useful information or patterns of data from large databases. Data mining is a computer-assisted process of digging and analyzing enormous sets of data and then extracting the desired information or data. Data mining tools also predict behaviors and future trends, allowing businesses to make proactive, knowledge-driven decisions. There are two types of data mining techniques; descriptive data mining that describes the general properties of the existing data, and predictive data mining that attempts to do predictions based on inferences on available data. The patterns obtained are used to describe concepts, to analyze associations, to build classification and regression models, to cluster data, to model trends in time-series and to detect outliers ("data objects that do not comply with the general behavior or model of the data"). Since the patterns which are present in data are not all equally useful and interesting, measures are needed to estimate the relevance of the discovered patterns to guide the mining process. The data mining software performs an analysis of relationships and patterns in stored transaction data based on open-ended user queries.