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An unsupervised recommender system for smart homes
KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.
2014 (English)In: Journal of Ambient Intelligence and Smart Environments, ISSN 1876-1364, Vol. 6, no 1, 21-37 p.Article in journal (Refereed) Published
Abstract [en]

Inhabitants of today's smarter homes struggle with complicated user interfaces and inflexible home configurations. The proposed smart home recommender system addresses these issues by continuously interpreting the user's current situation and recommending services that fit the user's habits, i.e. automate some action that the user would want to perform anyway. With these recommendations it is possible to build much simpler user interfaces that highlight the most interesting choices currently available. Configuration becomes much more flexible, since the recommender system automatically learns user habits. Evaluations on two smart home datasets show that the algorithm produces correct recommendations with 61% and 73% accuracy, respectively.

Place, publisher, year, edition, pages
2014. Vol. 6, no 1, 21-37 p.
Keyword [en]
behavior modeling, Context-awareness, service discovery, unsupervised learning
National Category
Computer Science
URN: urn:nbn:se:kth:diva-142784DOI: 10.3233/AIS-130242ISI: 000331301200004ScopusID: 2-s2.0-84893914483OAI: diva2:704680

QC 20140313

Available from: 2014-03-13 Created: 2014-03-12 Last updated: 2014-03-25Bibliographically approved

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Rasch, Katharina
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