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 language||English (US)|
|Title of host publication||RecSys 2020 - 14th ACM Conference on Recommender Systems|
|Publisher||Association for Computing Machinery, Inc|
|Number of pages||3|
|State||Published - Sep 22 2020|
|Event||14th ACM Conference on Recommender Systems, RecSys 2020 - Virtual, Online, Brazil|
Duration: Sep 22 2020 → Sep 26 2020
|Name||RecSys 2020 - 14th ACM Conference on Recommender Systems|
|Conference||14th ACM Conference on Recommender Systems, RecSys 2020|
|Period||9/22/20 → 9/26/20|
Bibliographical notePublisher Copyright:
© 2020 Owner/Author.
- Context-Aware Recommendation
- Contextual Modeling
- Sequence-Aware Recommendation