The Effect of Context on the Predictive Performance of Segmentation
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 03
User profiling with hierarchical context: an e-Retailer case study
CONTEXT'07 Proceedings of the 6th international and interdisciplinary conference on Modeling and using context
A Multi-agent System Using Ontological User Profiles for Dynamic User Modelling
WI-IAT '11 Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Volume 01
Using context to improve the effectiveness of segmentation and targeting in e-commerce
Expert Systems with Applications: An International Journal
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The idea that context is important when predicting customer behavior has been maintained by scholars in marketing and data mining. However, no systematic study measuring how much the contextual information really matters in building customer models in personalization applications have been done before. In this paper, we address this problem. To this aim, we collected data containing rich contextual information by developing a special-purpose browser to help users to navigate a well-known e-commerce retail portal and purchase products on its site. The experimental results show that context does matter for the case of modeling behavior of individual customers. The granularity of contextual information also matters, and the effect of contextual information gets diluted during the process of aggregating customers' data.