Workshop on context-aware recommender systems (CARS) 2021

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish (US)
Title of host publicationRecSys 2021 - 15th ACM Conference on Recommender Systems
PublisherAssociation for Computing Machinery, Inc
Pages813-814
Number of pages2
ISBN (Electronic)9781450384582
DOIs
StatePublished - Sep 13 2021
Event15th ACM Conference on Recommender Systems, RecSys 2021 - Virtual, Online, Netherlands
Duration: Sep 27 2021Oct 1 2021

Publication series

NameRecSys 2021 - 15th ACM Conference on Recommender Systems

Conference

Conference15th ACM Conference on Recommender Systems, RecSys 2021
Country/TerritoryNetherlands
CityVirtual, Online
Period9/27/2110/1/21

Bibliographical note

Publisher Copyright:
© 2021 Owner/Author.

Keywords

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

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