A Dataset for Inferring Contextual Preferences of Users Watching TV

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Abstrakt

Studies have shown that contextual settings play an important role in users' decision processes of what to consume, but data supporting the investigation of context-aware recommender systems are scarce. In this paper we present a TV consumption dataset enriched with contextual information of viewing situations. The dataset is designed for studying the intrinsic complexity of TV watching activities, and hence we also evaluate the performance of predicting chosen genres given contextual settings, and compare the results to contextless predictions. The results suggest a significant improvement by including contextual features in the prediction.
OriginalsprogEngelsk
TitelUMAP 2018 - Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization : UMAP '18
Antal sider2
UdgivelsesstedSingapore, Singapore
ForlagAssociation for Computing Machinery
Publikationsdato3 jul. 2018
Sider367-368
ISBN (Trykt)978-1-4503-5589-6/18/07
ISBN (Elektronisk)9781450355896
DOI
StatusUdgivet - 3 jul. 2018
Begivenhed the 26th Conference on User Modeling, Adaptation and Personalization: U`Map 18 - Singapore, Singapore
Varighed: 8 jul. 201811 jun. 2019

Konference

Konference the 26th Conference on User Modeling, Adaptation and Personalization
Land/OmrådeSingapore
BySingapore
Periode08/07/201811/06/2019

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