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Sales Strategy Mining Support with Visualization of Moving History
Authors:Haruhi Satonaka  Wataru Sunayama
Institution:1. Graduate School of Information Sciences, Hiroshima City University, 3-4-1, Ozuka-Higashi, Asa-Minami-ku, Hiroshima, 731-3194, Japan
Abstract:Strategic usage in data mining of sales data has come under increased focus as a result of the growth of data mining studies using electrical data, such as Point of Sale (POS) data. However, many of these mining systems only output results such as frequently appearing patterns, while, instead, they should be aimed at people who mine data. In this paper, a framework for leading and supporting new ideas from data is introduced. Based on this framework, a system that supports strategic usage in the data mining of sales data is proposed. The system deals not only with POS data, but also with the moving history of each customer. The system visualizes POS and moving history data, so that an analyzer inputs conditions to narrow down customers and acquires customer features. In addition to the ordinal outputs of a mining system, the analyzer interprets the meaning of his/her input and output to create a new strategy based on the framework. According to the experimental results, new strategies derived from the moving history were created.
Keywords:
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