Home > Research > Publications & Outputs > Strategies for avoiding preference profiling in...

Research

Associated organisational units

Electronic data

  • Strategies for ecommerce

    Rights statement: The original publication is available at www.link.springer.com

    Submitted manuscript, 1.05 MB, PDF document

Links

Text available via DOI:

Keywords

View graph of relations

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

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Published

Standard

Strategies for avoiding preference profiling in agent-based e-commerce environments. / Serrano, Emilio; Such, Jose M.; Garcia-Fornes, Ana et al.
In: Applied Intelligence, Vol. 40, No. 1, 01.2014, p. 127-142.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Serrano, E, Such, JM, Garcia-Fornes, A & Botia, J 2014, 'Strategies for avoiding preference profiling in agent-based e-commerce environments', Applied Intelligence, vol. 40, no. 1, pp. 127-142. https://doi.org/10.1007/s10489-013-0448-2

APA

Serrano, E., Such, J. M., Garcia-Fornes, A., & Botia, J. (2014). Strategies for avoiding preference profiling in agent-based e-commerce environments. Applied Intelligence, 40(1), 127-142. https://doi.org/10.1007/s10489-013-0448-2

Vancouver

Serrano E, Such JM, Garcia-Fornes A, Botia J. Strategies for avoiding preference profiling in agent-based e-commerce environments. Applied Intelligence. 2014 Jan;40(1):127-142. Epub 2013 Jun 1. doi: 10.1007/s10489-013-0448-2

Author

Serrano, Emilio ; Such, Jose M. ; Garcia-Fornes, Ana et al. / Strategies for avoiding preference profiling in agent-based e-commerce environments. In: Applied Intelligence. 2014 ; Vol. 40, No. 1. pp. 127-142.

Bibtex

@article{2a612494e21941e69a14452224009f14,
title = "Strategies for avoiding preference profiling in agent-based e-commerce environments",
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.",
keywords = "privacy, agent-based e-commerce , preference profiling, interaction analysis, data mining",
author = "Emilio Serrano and Such, {Jose M.} and Ana Garcia-Fornes and Juan Botia",
note = "The original publication is available at www.link.springer.com",
year = "2014",
month = jan,
doi = "10.1007/s10489-013-0448-2",
language = "English",
volume = "40",
pages = "127--142",
journal = "Applied Intelligence",
issn = "0924-669X",
publisher = "Springer Netherlands",
number = "1",

}

RIS

TY - JOUR

T1 - Strategies for avoiding preference profiling in agent-based e-commerce environments

AU - Serrano, Emilio

AU - Such, Jose M.

AU - Garcia-Fornes, Ana

AU - Botia, Juan

N1 - The original publication is available at www.link.springer.com

PY - 2014/1

Y1 - 2014/1

N2 - 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.

AB - 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.

KW - privacy

KW - agent-based e-commerce

KW - preference profiling

KW - interaction analysis

KW - data mining

U2 - 10.1007/s10489-013-0448-2

DO - 10.1007/s10489-013-0448-2

M3 - Journal article

VL - 40

SP - 127

EP - 142

JO - Applied Intelligence

JF - Applied Intelligence

SN - 0924-669X

IS - 1

ER -