Workshop on Context-Aware Recommender Systems (CARS) 2021
Authors: 
Gediminas Adomavicius, Konstantin Bauman, Bamshad Mobasher, 
Francesco Ricci, Alexander Tuzhilin, Moshe UngerAuthors Info & Claims
Gediminas Adomavicius, Konstantin Bauman, Bamshad Mobasher, Francesco Ricci, Alexander Tuzhilin, Moshe UngerAuthors Info & ClaimsPages 813 - 814
Abstract
Contextual information has been widely recognized as an important modeling dimension both 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 2021 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.
References
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Gediminas Adomavicius and Alexander Tuzhilin. 2015. Context-aware recommender systems. In Recommender systems handbook. Springer, 191–226.
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Xichen Ding, Jie Tang, Tracy Liu, Cheng Xu, Yaping Zhang, Feng Shi, Qixia Jiang, and Dan Shen. 2019. Infer Implicit Contexts in Real-time Online-to-Offline Recommendation. In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. 2336–2346.
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Negar Hariri, Bamshad Mobasher, and Robin Burke. 2012. Context-aware music recommendation based on latenttopic sequential patterns. In Proceedings of the sixth ACM conference on Recommender systems. ACM, 131–138.
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David Massimo and Francesco Ricci. 2018. Harnessing a generalised user behaviour model for next-POI recommendation. In Proceedings of the 12th ACM Conference on Recommender Systems, RecSys 2018, Vancouver, BC, Canada, October 2-7, 2018. 402–406. https://doi.org/10.1145/3240323.3240392
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- Workshop on Context-Aware Recommender Systems (CARS) 2021
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Information & Contributors
Information
Published In
September 2021
883 pages
ISBN:9781450384582
DOI:10.1145/3460231
Copyright © 2021 Owner/Author.
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.
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- SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web
- SIGAI: ACM Special Interest Group on Artificial Intelligence
- SIGKDD: ACM Special Interest Group on Knowledge Discovery in Data
- SIGIR: ACM Special Interest Group on Information Retrieval
- SIGCHI: ACM Special Interest Group on Computer-Human Interaction
- SIGecom: Special Interest Group on Economics and Computation
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 13 September 2021
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- Extended-abstract
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- Refereed limited
Conference
RecSys '21: Fifteenth ACM Conference on Recommender Systems
September 27 - October 1, 2021
Amsterdam, Netherlands
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Overall Acceptance Rate 254 of 1,295 submissions, 20%
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