Strategies for avoiding preference profiling in agent-based e-commerce environments

Serrano, Emilio and Such, Jose M. and Garcia-Fornes, Ana and Botia, Juan (2014) Strategies for avoiding preference profiling in agent-based e-commerce environments. Applied Intelligence, 40 (1). pp. 127-142. ISSN 0924-669X

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Abstract

Agent-based electronic commerce is known to offer many advantages to users. However, very few studies have been devoted to deal with privacy issues in this domain. Nowadays, privacy is of great concern and preserving users' privacy plays a crucial role to promote their trust in agent-based technologies. In this paper, we focus on preference profiling, which is a well-known threat to users' privacy. Specifically, we review strategies for customers' agents to prevent seller agents from obtaining accurate preference proles of the former group by using data mining techniques. We experimentally show the efficacy of each of these strategies and discuss their suitability in different situations. Our experimental results show that customers can improve their privacy notably with these strategies.

Item Type:
Journal Article
Journal or Publication Title:
Applied Intelligence
Additional Information:
The original publication is available at www.link.springer.com
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/1700/1702
Subjects:
ID Code:
64363
Deposited By:
Deposited On:
08 May 2013 12:58
Refereed?:
Yes
Published?:
Published
Last Modified:
27 Sep 2020 01:48