Workshop on Context-Aware Recommender Systems (CARS) 2024

Gediminas Adomavicius, Konstantin Bauman, Bamshad Mobasher, 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 2024 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 2024 - Proceedings of the 18th ACM Conference on Recommender Systems
PublisherAssociation for Computing Machinery, Inc
Pages1219-1221
Number of pages3
ISBN (Electronic)9798400705052
DOIs
StatePublished - 8 Oct 2024
Event18th ACM Conference on Recommender Systems, RecSys 2024 - Bari, Italy
Duration: 14 Oct 202418 Oct 2024

Publication series

NameRecSys 2024 - Proceedings of the 18th ACM Conference on Recommender Systems

Conference

Conference18th ACM Conference on Recommender Systems, RecSys 2024
Country/TerritoryItaly
CityBari
Period14/10/2418/10/24

Keywords

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

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