Interactive Datamining Process Based on Human-Centered System for Banking Marketing Applications
نویسندگان
چکیده
Knowledge Discovery in Databases (KDD) is the new hope for marketing due to the increasing collection of large databases. There is a paradox because the companies must improve the development policy of customer loyalty by using methods that do not allow to treat large quantities of data. Our current work is the results of a study that we led on a association rules mining in banking marketing problem. Our first encouraging results steered our work towards a hierarchical association rules mining, using a user-driven approach rather than an automatic approach. The user is at the heart of the process, playing a role of evolutionary heuristic. Mining process is oriented according to intermediate expert’s choices. The final aim of our approach is to use the advantages of the methods to decrease both number of generated rules and expertise time. This paper presents the results of our research step for including the user into datamining process.
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