Collective embedding for neural context-aware recommender systems

Felipe Soares Da Costa, Peter Dolog

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

14 Citationer (Scopus)


Context-aware recommender systems consider contextual features as additional information to predict user's preferences. For example, the recommendations could be based on time, location, or the company of other people. Among the contextual information, time became an important feature because user preferences tend to change over time or be similar in the near future. Researchers have proposed diferent models to incorporate time into their recommender system, however, the current models are not able to capture specifc temporal patterns. To address the limitation observed in previous works, we propose Collective embedding for Neural Context-Aware Recommender Systems (CoNCARS). The proposed solution jointly model the item, user and time embeddings to capture temporal patterns. Then, CoNCARS use the outer product to model the user-item-time correlations between dimensions of the embedding space. The hidden features feed our Convolutional Neural Networks (CNNs) to learn the non-linearities between the diferent features. Finally, we combine the output from our CNNs in the fusion layer and then predict the user's preference score. We conduct extensive experiments on real-world datasets, demonstrating CoNCARS improves the top-N item recommendation task and outperform the state-of-the-art recommendation methods.

TitelProceedings of the 13th ACM Conference on Recommender Systems, RecSys 2019, Copenhagen, Denmark, September 16-20, 2019.
RedaktørerToine Bogers, Alan Said, Peter Brusilovsky, Domonkos Tikk
Antal sider9
ForlagAssociation for Computing Machinery
ISBN (Trykt)978-1-4503-6243-6
ISBN (Elektronisk)9781450362436
StatusUdgivet - 2019
BegivenhedRecSys 2019: 13th ACM Conference on Recommender Systems - Copenhagen, Denmark, Copenhagen, Danmark
Varighed: 16 sep. 201820 sep. 2018
Konferencens nummer: 13


KonferenceRecSys 2019: 13th ACM Conference on Recommender Systems
LokationCopenhagen, Denmark


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