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User evaluation of a market-based recommender system
OA Location
Author(s)
Wei, YZ
Jennings, NR
Moreau, L
Hall, W
Type
Journal Article
Abstract
Recommender systems have been developed for a wide variety of applications (ranging from books, to holidays, to web pages). These systems have used a number of different approaches, since no one technique is best for all users in all situations. Given this, we believe that to be effective, systems should incorporate a wide variety of such techniques and then some form of overarching framework should be put in place to coordinate them so that only the best recommendations (from whatever source) are presented to the user. To this end, in our previous work, we detailed a market-based approach in which various recommender agents competed with one another to present their recommendations to the user. We showed through theoretical analysis and empirical evaluation with simulated users that an appropriately designed marketplace should be able to provide effective coordination. Building on this, we now report on the development of this multi-agent system and its evaluation with real users. Specifically, we show that our system is capable of consistently giving high quality recommendations, that the best recommendations that could be put forward are actually put forward, and that the combination of recommenders performs better than any constituent recommender.
Date Issued
2008-01-30
Date Acceptance
2008-01-30
Citation
Autonomous Agents and Multi-Agent Systems, 2008, 17 (2), pp.251-269
URI
DOI
ISSN
1573-7454
Publisher
Springer Verlag
Start Page
251
End Page
269
Journal / Book Title
Autonomous Agents and Multi-Agent Systems
Volume
17
Issue
2
Copyright Statement
© Springer Verlag 2008. The final publication is available at Springer via http://dx.doi.org/10.1007/s10458-008-9029-x
Subjects
Science & Technology
Technology
Automation & Control Systems
Computer Science, Artificial Intelligence
Computer Science
AUTOMATION & CONTROL SYSTEMS
COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
recommender systems
auctions
marketplace
user evaluation
Artificial Intelligence & Image Processing
0801 Artificial Intelligence And Image Processing
1702 Cognitive Science
Publication Status
Published