Empirical Methodology and Innovative Algorithm for Mining High Utility Itemset on Temporal Data

Abstract

Ever since the humans found the significance of data we are using different methodologies to extricate data patterns in the most useful way to reach at various conclusions based on our needs. The proper utilization of data will leads to meaning full results. Here our focus is to expand the concept of "High utility itemset mining" and also introducing the concept of "timestamp" on it. Here we proposed an effective algorithm to find the best possible data patterns that generate maximum profit within the given "time period" and also proposed a new framework to calculate the "utility support”. Our analysis can be utilized to improve profitability in business and also make better decisions for improving sales in the organization.