Workshop on Context-Aware Recommender Systems

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

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


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 2020 workshop provides a venue for presenting and discussing approaches for 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 online environments.

Original languageEnglish
Title of host publicationRecSys 2020 - 14th ACM Conference on Recommender Systems
PublisherAssociation for Computing Machinery, Inc
Number of pages3
ISBN (Electronic)9781450375832
StatePublished - 22 Sep 2020
Externally publishedYes
Event14th ACM Conference on Recommender Systems, RecSys 2020 - Virtual, Online, Brazil
Duration: 22 Sep 202026 Sep 2020

Publication series

NameRecSys 2020 - 14th ACM Conference on Recommender Systems


Conference14th ACM Conference on Recommender Systems, RecSys 2020
CityVirtual, Online


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


Dive into the research topics of 'Workshop on Context-Aware Recommender Systems'. Together they form a unique fingerprint.

Cite this