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 contributionpeer-review

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
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 - 12 Sep 2022
Externally publishedYes
Event16th ACM Conference on Recommender Systems, RecSys 2022 - Seattle, United States
Duration: 18 Sep 202223 Sep 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
Period18/09/2223/09/22

Keywords

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

ASJC Scopus subject areas

  • Hardware and Architecture
  • Software

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