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Layered evaluation for data discovery and recommendation systems: An initial set of principles
dc.creator | Manouselis, N. | en |
dc.creator | Karagiannidis, C. | en |
dc.creator | Sampson, D. G. | en |
dc.date.accessioned | 2015-11-23T10:38:46Z | |
dc.date.available | 2015-11-23T10:38:46Z | |
dc.date.issued | 2014 | |
dc.identifier | 10.1109/ICALT.2014.152 | |
dc.identifier.isbn | 9781479940387 | |
dc.identifier.uri | http://hdl.handle.net/11615/30661 | |
dc.description.abstract | This paper examines how a layered evaluation framework proposed for adaptive systems (AS) can be applied in the case of recommender systems (RecSys). Our analysis indicates that implementing a layered-based evaluation has the potential to facilitate a more detailed and informed evaluation of RecSys, allowing researchers and developers to better understand how to improve them. © 2014 IEEE. | en |
dc.source.uri | http://www.scopus.com/inward/record.url?eid=2-s2.0-84910069393&partnerID=40&md5=c46a2d771e48549c688f6fcce79e18f2 | |
dc.subject | adaptive systems | en |
dc.subject | layered evaluation | en |
dc.subject | recommender systems | en |
dc.subject | Data discovery | en |
dc.title | Layered evaluation for data discovery and recommendation systems: An initial set of principles | en |
dc.type | conferenceItem | en |
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