Journal
EXPERT SYSTEMS WITH APPLICATIONS
Volume 41, Issue 10, Pages 4648-4657Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2014.01.022
Keywords
Clustering; Sequence mining; Business knowledge; Behavior process; Trajectories; Direct marketing
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Funding
- Ticketmatic and the Flemish Research Council
- Ticketmatic Research Chair in Cultural Data Analytics
- FWO postdoctoral research grant: Odysseus [B.0915.09]
- KU Leuven research council [OT/10/010]
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In this paper, a novel approach towards enabling the exploratory understanding of the dynamics inherent in the capture of customers' data at different points in time is outlined. The proposed methodology combines state-of-art data mining clustering techniques with a tuned sequence mining method to discover prominent customer behavior trajectories in data bases, which - when combined - represent the behavior process as it is followed by particular groups of customers. The framework is applied to a real-life case of an event organizer; it is shown how behavior trajectories can help to explain consumer decisions and to improve business processes that are influenced by customer actions. (C) 2014 Elsevier Ltd. All rights reserved.
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