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User evaluation of a market-based recommender system

User evaluation of a market-based recommender system
User evaluation of a market-based recommender system
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
recommender systems, auctions, marketplace, user evaluation
1387-2532
251-269
Wei, Yan Zheng
a5d942b8-a744-482a-949b-a95b5a47cf68
Jennings, Nicholas R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30
Moreau, Luc
033c63dd-3fe9-4040-849f-dfccbe0406f8
Hall, Wendy
11f7f8db-854c-4481-b1ae-721a51d8790c
Wei, Yan Zheng
a5d942b8-a744-482a-949b-a95b5a47cf68
Jennings, Nicholas R.
ab3d94cc-247c-4545-9d1e-65873d6cdb30
Moreau, Luc
033c63dd-3fe9-4040-849f-dfccbe0406f8
Hall, Wendy
11f7f8db-854c-4481-b1ae-721a51d8790c

Wei, Yan Zheng, Jennings, Nicholas R., Moreau, Luc and Hall, Wendy (2008) User evaluation of a market-based recommender system. Autonomous Agents and Multi-Agent Systems, 17 (2), 251-269. (doi:10.1007/s10458-008-9029-x).

Record type: 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

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More information

Published date: 1 October 2008
Keywords: recommender systems, auctions, marketplace, user evaluation
Organisations: Web & Internet Science, Agents, Interactions & Complexity

Identifiers

Local EPrints ID: 265015
URI: http://eprints.soton.ac.uk/id/eprint/265015
ISSN: 1387-2532
PURE UUID: ad40733c-62e2-430c-aa32-0f82fa1fc4e3
ORCID for Luc Moreau: ORCID iD orcid.org/0000-0002-3494-120X
ORCID for Wendy Hall: ORCID iD orcid.org/0000-0003-4327-7811

Catalogue record

Date deposited: 08 Jan 2008 08:08
Last modified: 17 Dec 2019 02:04

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Contributors

Author: Yan Zheng Wei
Author: Nicholas R. Jennings
Author: Luc Moreau ORCID iD
Author: Wendy Hall ORCID iD

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