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

doi:10.1007/s10489-013-0448-2

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

2013-06-13

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AI

DOI：10.1007/s10489-013-0448-2

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Abstract

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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. 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 profiles 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.

Keywords:

Privacy

Agent-based e-commerce

Preference profiling

Interaction analysis

Data mining

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

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