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In this paper, we use reinforcement learning (RL) techniques to determine dynamic prices in an electronic monopolistic retail market. The market that we consider consists of two natural segments of customers, captives and shoppers. Captives are mature, loyal buyers whereas the shoppers are more price sensitive and are attracted by sales promotions and(More)
Many organizations have collected large amounts of spatially referenced data in various application areas such as geographic information systems (GIS), banking and retailing. These are valuable mines of knowledge vital for strategic decision making and motivate the highly demanding field of spatial data mining i.e., discovery of interesting, implicit(More)
The Cloud resource procurement of cloud resources is an interesting and yet unexplored area in cloud computing. cloud vendors choose a fixed pricing strategy for pricing their resources and do not provide any incentive to their users. That's why to choose only automates the selection of an appropriate cloud vendor and also to implement the dynamic pricing.(More)
Marketing decisions are typically made on the basis of research conducted using direct mailings, mall intercepts, telephone interviews, focused group discussion, and the like. These methods of marketing research can be time-consuming and expensive, and can require a large amount of effort to ensure accurate results. This paper presents a novel approach for(More)
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