A comparison of calibrated and intent-aware recommendations

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dc.contributor.author Kaya, Mesut
dc.contributor.author Bridge, Derek G.
dc.date.accessioned 2019-11-08T12:22:37Z
dc.date.available 2019-11-08T12:22:37Z
dc.date.issued 2019-09
dc.identifier.citation Kaya, M. and Bridge, D. (2019) 'A comparison of calibrated and intent-aware recommendations', RecSys '19: Proceedings of the 13th ACM Conference on Recommender Systems, Copenhagen, Denmark, 16-20 September, pp. 151-159. doi: 10.1145/3298689.3347045 en
dc.identifier.startpage 151 en
dc.identifier.endpage 159 en
dc.identifier.isbn 978-1-4503-6243-6
dc.identifier.uri http://hdl.handle.net/10468/8978
dc.identifier.doi 10.1145/3298689.3347045 en
dc.description.abstract Calibrated and intent-aware recommendation are recent approaches to recommendation that have apparent similarities. Both try, to a certain extent, to cover the user's interests, as revealed by her user profile. In this paper, we compare them in detail. On two datasets, we show the extent to which intent-aware recommendations are calibrated and the extent to which calibrated recommendations are diverse. We consider two ways of defining a user's interests, one based on item features, the other based on subprofiles of the user's profile. We find that defining interests in terms of subprofiles results in highest precision and the best relevance/diversity trade-off. Along the way, we define a new version of calibrated recommendation and three new evaluation metrics. en
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.publisher Association for Computing Machinery (ACM) en
dc.relation.uri https://recsys.acm.org/recsys19/
dc.rights © 2019, Association for Computing Machinery. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in RecSys '19: Proceedings of the 13th ACM Conference on Recommender Systems, Copenhagen, Denmark, 16-20 September, pp. 151-159. http://dx.doi.org/10.1145/3298689.3347045 en
dc.subject Calibration en
dc.subject Intent-aware en
dc.subject Diversity en
dc.title A comparison of calibrated and intent-aware recommendations en
dc.type Conference item en
dc.internal.authorcontactother Derek Bridge, Computer Science, University College Cork, Cork, Ireland. +353-21-490-3000 Email: d.bridge@cs.ucc.ie en
dc.internal.availability Full text available en
dc.date.updated 2019-11-08T12:09:06Z
dc.description.version Accepted Version en
dc.internal.rssid 499911632
dc.contributor.funder Science Foundation Ireland en
dc.description.status Peer reviewed en
dc.internal.copyrightchecked Yes
dc.internal.licenseacceptance Yes en
dc.internal.conferencelocation Copenhagen, Denmark en
dc.internal.IRISemailaddress d.bridge@cs.ucc.ie en
dc.relation.project info:eu-repo/grantAgreement/SFI/SFI Research Centres/12/RC/2289/IE/INSIGHT - Irelands Big Data and Analytics Research Centre/ en

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