CARS: Workshop on Context-Aware Recommender Systems 2023

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

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

2 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 2023 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 publicationProceedings of the 17th ACM Conference on Recommender Systems, RecSys 2023
PublisherAssociation for Computing Machinery, Inc
Pages1234-1236
Number of pages3
ISBN (Electronic)9798400702419
DOIs
StatePublished - Sep 14 2023
Event17th ACM Conference on Recommender Systems, RecSys 2023 - Singapore, Singapore
Duration: Sep 18 2023Sep 22 2023

Publication series

NameProceedings of the 17th ACM Conference on Recommender Systems

Conference

Conference17th ACM Conference on Recommender Systems, RecSys 2023
Country/TerritorySingapore
CitySingapore
Period9/18/239/22/23

Bibliographical note

Publisher Copyright:
© 2023 Owner/Author.

Keywords

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

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