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Customer Profiling in Complex Analytical Environments Using Swarm Intelligence Algorithms

Customer Profiling in Complex Analytical Environments Using Swarm Intelligence Algorithms
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Author(s): Goran Klepac (Raiffeisenbank Austria d.d., Croatia)
Copyright: 2017
Pages: 32
Source title: Nature-Inspired Computing: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-5225-0788-8.ch053

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Abstract

Customer profiling is always an interesting task from perspective of business. It became even bigger challenge in situation of complex analytical environment. Complex analytical environment can be caused by multiple modality of output variable as well as from big data environment, which cause data complexity in way of data quantity. As an illustration of presented concept particle swarm optimization algorithm will be used as a tool, which will find profiles from developed predictive model of neural network. Presented methodology has practical value for decision support in business, where information about customer profiles which prefers to buy some product or group products are valuable information for campaign planning and customer portfolio management.

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