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Research Paper | Computer Science & Engineering | Bangladesh | Volume 6 Issue 2, February 2017

Mining Weighted Association Rules Using Probabilistic and Combinational Approach

A I Liton | M A Rahman | T Rahman

Abstract: Association Rule Mining (ARM) is one of the most popular data mining techniques. Weight Association rule mining (WARM) is adapted to handle weighted associated mining problems where each item is allowed to have a weight. The goal is to steer the mining focus to those significant relationships involving items with significant weights rather than being flooded in the combinatorial explosion of insignificant relationships. Predictive models developed by applying Data Mining techniques are used to improve forecasting accuracy in the airline business. In this paper, we apply data mining techniques to real airline frequent flyer data in order to derive customer relationship and recommendations. We are going to introduce a new measure using HIPRO & Apriori algorithm, on the passenger database system of an Airline.

Keywords: Data Mining, Weight Association Rules, WARM, Probabilistic, HIPRO

Edition: Volume 6 Issue 2, February 2017,

Pages: 475 - 479