title: |
Association-rule-based User Segmenta-tion: An Empirical Study |
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publication: |
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part of series: |
Advances in Intelligent Systems Research | |
ISBN: |
978-90-78677-40-6 | |
ISSN: |
1951-6851 | |
DOI: |
doi:10.2991/icebi.2010.33 (how to use a DOI) | |
author(s): |
Ming Ren, Qiang Wei, Wei Xu |
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publication date: |
December 2010 |
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keywords: |
segmentation, association
rule, the Entity-Relationship (ER) model,
understandability, empirical study |
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abstract: |
Segmentation is becoming crucial than
ever for proper exploration of information
and delivery of services to the users in a
personalized manner. This paper proposes
a user segmentation method based on association rules discovered in large databases, and represents the hierarchical
segmentation by the Entity-Relationship
model, which is easy to understand. To
evaluate the proposed model, the understandability of the model is studied from
the perspective of a modeler. The experiment result shows that the models were
understandable and richer in semantics,
and that the level of segmentation hierarchy might affect the degree of understandability. |
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copyright: |
©
Atlantis Press. This article is distributed under the
terms of the Creative Commons Attribution License, which permits
non-commercial use, distribution and reproduction in any medium,
provided the original work is properly cited. |
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full text: |