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 proceedingConference contribution

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 languageEnglish (US)
Title of host publicationRecSys 2022 - Proceedings of the 16th ACM Conference on Recommender Systems
PublisherAssociation for Computing Machinery, Inc
Pages691-693
Number of pages3
ISBN (Electronic)9781450392785
DOIs
StatePublished - Sep 12 2022
Event16th ACM Conference on Recommender Systems, RecSys 2022 - Seattle, United States
Duration: Sep 18 2022Sep 23 2022

Publication series

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

Conference

Conference16th ACM Conference on Recommender Systems, RecSys 2022
Country/TerritoryUnited States
CitySeattle
Period9/18/229/23/22

Bibliographical note

Publisher Copyright:
© 2022 Owner/Author.

Keywords

  • Context
  • Context-Aware Recommendation
  • Contextual Modeling
  • Sequence-Aware Recommendation

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