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http://hdl.handle.net/1942/27943
Title: | Customer Segmentation Using Multiple Instance Clustering and Purchasing Behaviors | Authors: | FUENTES HERRERA, Ivett NAPOLES RUIZ, Gonzalo Arco, Leticia VANHOOF, Koen |
Issue Date: | 2018 | Publisher: | SPRINGER INTERNATIONAL PUBLISHING AG | Source: | Hernández Heredia, Y.; Milián Núñez, V.; Ruiz Shulcloper, J. (Ed.). Progress in Artificial Intelligence and Pattern Recognition 6th International Workshop, IWAIPR 2018, Havana, Cuba, September 24–26, 2018, Proceedings, SPRINGER INTERNATIONAL PUBLISHING AG,p. 193-200 | Series/Report: | Image Processing, Computer Vision, Pattern Recognition, and Graphics | Series/Report no.: | 11047 | Abstract: | On-line companies usually maintain complex information systems for capturing records about Customer Purchasing Behaviors (CPBs) in a cost-effective manner. Building prediction models from this data is considered a crucial step of most Decision Support Systems used in business informatics. Segmentation of similar CPB is an example of such an analysis. However, existing methods do not consider a strategy for quantifying the interactions between customers taking into account all entities involved in the problem. To tackle this issue, we propose a customer segmentation approach based on their CPB profile and multiple instance clustering. More specifically, we model each customer as an ordered bag comprised of instances, where each instance represents a transaction (order). Internal measures and modularity are adopted to evaluate the resultant segmentation, thus supporting the reliability of our model in business marketing analysis. | Notes: | Fuentes, I (reprint author), Cent Univ Las Villas, Dept Comp Sci, Santa Clara, Cuba. Hasselt Univ, Fac Business Econ, Hasselt, Belgium. ivett@uclv.cu | Keywords: | Multiple instance clustering; Customer Purchasing Behaviors; Decision Support Systems | Document URI: | http://hdl.handle.net/1942/27943 | ISBN: | 978-3-030-01131-4 978-3-030-01132-1 |
ISSN: | 0302-9743 | DOI: | 10.1007/978-3-030-01132-1_22 | ISI #: | WOS:000476932700022 | Category: | C1 | Type: | Proceedings Paper | Validations: | ecoom 2020 vabb 2020 |
Appears in Collections: | Research publications |
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segmentation.pdf Restricted Access | Peer-reviewed author version | 691.78 kB | Adobe PDF | View/Open Request a copy |
fuentes2018.pdf Restricted Access | Published version | 585.87 kB | Adobe PDF | View/Open Request a copy |
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