Combining Clustering Algorithms for Provide Marketing Policy in Electronic Stores

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Provided by: Academy & Industry Research Collaboration Center
Topic: Data Management
Format: PDF
One of the main challenges of electronic market is how to attract customers as various products and customers' preferences effect widely on it. In this paper, the authors have started to categorize electronic markets customers using k-means, En, farthest first algorithms to determine marketing policies and customer satisfaction and indicated that each algorithm either cover the weakness of cluster analyzing of other algorithms for some customers or integrated data of all algorithm analyses which provided detailed results of customers' behavioral methods and its relation with their shopping basket could finally lead them to more income and increased productivity using obtained analyses.
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