CARS: Workshop on Context-Aware Recommender Systems 2022

Gediminas Adomavicius; Konstantin Bauman; Bamshad Mobasher; Francesco Ricci; Alexander Tuzhilin; Moshe Unger

doi:10.1145/3523227.3547421

CARS: Workshop on Context-Aware Recommender Systems 2022

Gediminas Adomavicius, Konstantin Bauman, Bamshad Mobasher, Francesco Ricci, Alexander Tuzhilin, Moshe Unger

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

Contextual information has been widely recognized as an important modeling dimension in social sciences and in computing. In particular, the role of context has been recognized in enhancing recommendation results and retrieval performance. While a substantial amount of existing research has focused on context-aware recommender systems (CARS), many interesting problems remain under-explored. The CARS 2022 workshop provides a venue for presenting and discussing: the important features of the next generation of CARS; and application domains that may require the use of novel types of contextual information and cope with their dynamic properties in group recommendations and in online environments.

Original language	English
Title of host publication	RecSys 2022 - Proceedings of the 16th ACM Conference on Recommender Systems
Publisher	Association for Computing Machinery, Inc
Pages	691-693
Number of pages	3
ISBN (Electronic)	9781450392785
DOIs	https://doi.org/10.1145/3523227.3547421
State	Published - 12 Sep 2022
Externally published	Yes
Event	16th ACM Conference on Recommender Systems, RecSys 2022 - Seattle, United States Duration: 18 Sep 2022 → 23 Sep 2022

Publication series

Name	RecSys 2022 - Proceedings of the 16th ACM Conference on Recommender Systems

Conference

Conference	16th ACM Conference on Recommender Systems, RecSys 2022
Country/Territory	United States
City	Seattle
Period	18/09/22 → 23/09/22

Keywords

Context
Context-Aware Recommendation
Contextual Modeling
Sequence-Aware Recommendation

ASJC Scopus subject areas

Hardware and Architecture
Software

Access to Document

10.1145/3523227.3547421

Cite this

Adomavicius, G., Bauman, K., Mobasher, B., Ricci, F., Tuzhilin, A., & Unger, M. (2022). CARS: Workshop on Context-Aware Recommender Systems 2022. In RecSys 2022 - Proceedings of the 16th ACM Conference on Recommender Systems (pp. 691-693). (RecSys 2022 - Proceedings of the 16th ACM Conference on Recommender Systems). Association for Computing Machinery, Inc. https://doi.org/10.1145/3523227.3547421

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keywords = "Context, Context-Aware Recommendation, Contextual Modeling, Sequence-Aware Recommendation",

author = "Gediminas Adomavicius and Konstantin Bauman and Bamshad Mobasher and Francesco Ricci and Alexander Tuzhilin and Moshe Unger",

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year = "2022",

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doi = "10.1145/3523227.3547421",

language = "English",

series = "RecSys 2022 - Proceedings of the 16th ACM Conference on Recommender Systems",

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Adomavicius, G, Bauman, K, Mobasher, B, Ricci, F, Tuzhilin, A & Unger, M 2022, CARS: Workshop on Context-Aware Recommender Systems 2022. in RecSys 2022 - Proceedings of the 16th ACM Conference on Recommender Systems. RecSys 2022 - Proceedings of the 16th ACM Conference on Recommender Systems, Association for Computing Machinery, Inc, pp. 691-693, 16th ACM Conference on Recommender Systems, RecSys 2022, Seattle, United States, 18/09/22. https://doi.org/10.1145/3523227.3547421

CARS: Workshop on Context-Aware Recommender Systems 2022. / Adomavicius, Gediminas; Bauman, Konstantin; Mobasher, Bamshad et al.
RecSys 2022 - Proceedings of the 16th ACM Conference on Recommender Systems. Association for Computing Machinery, Inc, 2022. p. 691-693 (RecSys 2022 - Proceedings of the 16th ACM Conference on Recommender Systems).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - Contextual information has been widely recognized as an important modeling dimension in social sciences and in computing. In particular, the role of context has been recognized in enhancing recommendation results and retrieval performance. While a substantial amount of existing research has focused on context-aware recommender systems (CARS), many interesting problems remain under-explored. The CARS 2022 workshop provides a venue for presenting and discussing: the important features of the next generation of CARS; and application domains that may require the use of novel types of contextual information and cope with their dynamic properties in group recommendations and in online environments.

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KW - Context-Aware Recommendation

KW - Contextual Modeling

KW - Sequence-Aware Recommendation

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Adomavicius G, Bauman K, Mobasher B, Ricci F, Tuzhilin A, Unger M. CARS: Workshop on Context-Aware Recommender Systems 2022. In RecSys 2022 - Proceedings of the 16th ACM Conference on Recommender Systems. Association for Computing Machinery, Inc. 2022. p. 691-693. (RecSys 2022 - Proceedings of the 16th ACM Conference on Recommender Systems). doi: 10.1145/3523227.3547421

CARS: Workshop on Context-Aware Recommender Systems 2022

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

Access to Document

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