Modeling User Preferences and Mediating Agents in Electronic Commerce

M.M. Dastani, N. Jacobs, C.M. Jonker, J. Treur

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

An important ingredient in agent-mediated Electronic Commerce is the presence of intelligent mediating agents that assist Electronic Commerce participants (e.g., individual users, other agents, organisations). These mediating agents are in principle autonomous agents that will interact with their environments (e.g. other agents and web-servers) on behalf of participants who have delegated tasks to them. For mediating agents a (preference) model of participants is indispensable. In this paper, a generic mediating agent architecture is introduced. Furthermore, we discuss our view of user preference modeling and its need in agent-mediated electronic commerce. We survey the state of the art in the field of preference modeling and suggest that the preferences of electronic commerce participants can be modelled by learning from their behaviour. In particular, we employ an existing machine learning method called inductive logic programming (ILP). We argue that this method can be used by mediating agents to detect regularities in the behaviour of the involved participants and induce hypotheses about their preferences automatically. Finally, we discuss some advantages and disadvantages of using inductive logic programming as a method for learning user preferences and compare this method with other approaches.
Original languageEnglish
Title of host publicationAgent Mediated Electronic Commerce
EditorsF. Dignum, C. Sierra
Place of PublicationBerlijn
PublisherSpringer/Verlag
Pages164-196
ISBN (Electronic)978-3-540-44682-8
ISBN (Print)978-3-540-41671-5
DOIs
Publication statusPublished - 2001

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1991 LNAI

Fingerprint

Electronic commerce
Inductive logic programming (ILP)
Autonomous agents
Intelligent agents
Learning systems
Servers

Bibliographical note

Reeks en reeks nummer: Lecture Notes in AI, vol. 1991

Cite this

Dastani, M. M., Jacobs, N., Jonker, C. M., & Treur, J. (2001). Modeling User Preferences and Mediating Agents in Electronic Commerce. In F. Dignum, & C. Sierra (Eds.), Agent Mediated Electronic Commerce (pp. 164-196). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1991 LNAI). Berlijn: Springer/Verlag. https://doi.org/10.1007/3-540-44682-6_10
Dastani, M.M. ; Jacobs, N. ; Jonker, C.M. ; Treur, J. / Modeling User Preferences and Mediating Agents in Electronic Commerce. Agent Mediated Electronic Commerce. editor / F. Dignum ; C. Sierra. Berlijn : Springer/Verlag, 2001. pp. 164-196 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
@inproceedings{08a8d45fcf994ca78b966bb4e0a38a40,
title = "Modeling User Preferences and Mediating Agents in Electronic Commerce",
abstract = "An important ingredient in agent-mediated Electronic Commerce is the presence of intelligent mediating agents that assist Electronic Commerce participants (e.g., individual users, other agents, organisations). These mediating agents are in principle autonomous agents that will interact with their environments (e.g. other agents and web-servers) on behalf of participants who have delegated tasks to them. For mediating agents a (preference) model of participants is indispensable. In this paper, a generic mediating agent architecture is introduced. Furthermore, we discuss our view of user preference modeling and its need in agent-mediated electronic commerce. We survey the state of the art in the field of preference modeling and suggest that the preferences of electronic commerce participants can be modelled by learning from their behaviour. In particular, we employ an existing machine learning method called inductive logic programming (ILP). We argue that this method can be used by mediating agents to detect regularities in the behaviour of the involved participants and induce hypotheses about their preferences automatically. Finally, we discuss some advantages and disadvantages of using inductive logic programming as a method for learning user preferences and compare this method with other approaches.",
author = "M.M. Dastani and N. Jacobs and C.M. Jonker and J. Treur",
note = "Reeks en reeks nummer: Lecture Notes in AI, vol. 1991",
year = "2001",
doi = "10.1007/3-540-44682-6_10",
language = "English",
isbn = "978-3-540-41671-5",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer/Verlag",
pages = "164--196",
editor = "F. Dignum and C. Sierra",
booktitle = "Agent Mediated Electronic Commerce",

}

Dastani, MM, Jacobs, N, Jonker, CM & Treur, J 2001, Modeling User Preferences and Mediating Agents in Electronic Commerce. in F Dignum & C Sierra (eds), Agent Mediated Electronic Commerce. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 1991 LNAI, Springer/Verlag, Berlijn, pp. 164-196. https://doi.org/10.1007/3-540-44682-6_10

Modeling User Preferences and Mediating Agents in Electronic Commerce. / Dastani, M.M.; Jacobs, N.; Jonker, C.M.; Treur, J.

Agent Mediated Electronic Commerce. ed. / F. Dignum; C. Sierra. Berlijn : Springer/Verlag, 2001. p. 164-196 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1991 LNAI).

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

TY - GEN

T1 - Modeling User Preferences and Mediating Agents in Electronic Commerce

AU - Dastani, M.M.

AU - Jacobs, N.

AU - Jonker, C.M.

AU - Treur, J.

N1 - Reeks en reeks nummer: Lecture Notes in AI, vol. 1991

PY - 2001

Y1 - 2001

N2 - An important ingredient in agent-mediated Electronic Commerce is the presence of intelligent mediating agents that assist Electronic Commerce participants (e.g., individual users, other agents, organisations). These mediating agents are in principle autonomous agents that will interact with their environments (e.g. other agents and web-servers) on behalf of participants who have delegated tasks to them. For mediating agents a (preference) model of participants is indispensable. In this paper, a generic mediating agent architecture is introduced. Furthermore, we discuss our view of user preference modeling and its need in agent-mediated electronic commerce. We survey the state of the art in the field of preference modeling and suggest that the preferences of electronic commerce participants can be modelled by learning from their behaviour. In particular, we employ an existing machine learning method called inductive logic programming (ILP). We argue that this method can be used by mediating agents to detect regularities in the behaviour of the involved participants and induce hypotheses about their preferences automatically. Finally, we discuss some advantages and disadvantages of using inductive logic programming as a method for learning user preferences and compare this method with other approaches.

AB - An important ingredient in agent-mediated Electronic Commerce is the presence of intelligent mediating agents that assist Electronic Commerce participants (e.g., individual users, other agents, organisations). These mediating agents are in principle autonomous agents that will interact with their environments (e.g. other agents and web-servers) on behalf of participants who have delegated tasks to them. For mediating agents a (preference) model of participants is indispensable. In this paper, a generic mediating agent architecture is introduced. Furthermore, we discuss our view of user preference modeling and its need in agent-mediated electronic commerce. We survey the state of the art in the field of preference modeling and suggest that the preferences of electronic commerce participants can be modelled by learning from their behaviour. In particular, we employ an existing machine learning method called inductive logic programming (ILP). We argue that this method can be used by mediating agents to detect regularities in the behaviour of the involved participants and induce hypotheses about their preferences automatically. Finally, we discuss some advantages and disadvantages of using inductive logic programming as a method for learning user preferences and compare this method with other approaches.

U2 - 10.1007/3-540-44682-6_10

DO - 10.1007/3-540-44682-6_10

M3 - Conference contribution

SN - 978-3-540-41671-5

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 164

EP - 196

BT - Agent Mediated Electronic Commerce

A2 - Dignum, F.

A2 - Sierra, C.

PB - Springer/Verlag

CY - Berlijn

ER -

Dastani MM, Jacobs N, Jonker CM, Treur J. Modeling User Preferences and Mediating Agents in Electronic Commerce. In Dignum F, Sierra C, editors, Agent Mediated Electronic Commerce. Berlijn: Springer/Verlag. 2001. p. 164-196. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/3-540-44682-6_10