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 underexplored. The CARS 2025 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 language | English (US) |
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| Title of host publication | RecSys2025 - Proceedings of the 19th ACM Conference on Recommender Systems |
| Publisher | Association for Computing Machinery, Inc |
| Pages | 1409-1411 |
| Number of pages | 3 |
| ISBN (Electronic) | 9798400713644 |
| DOIs | |
| State | Published - Aug 7 2025 |
| Event | 19th ACM Conference on Recommender Systems, RecSys 2025 - Prague, Czech Republic Duration: Sep 22 2025 → Sep 26 2025 |
Publication series
| Name | RecSys2025 - Proceedings of the 19th ACM Conference on Recommender Systems |
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Conference
| Conference | 19th ACM Conference on Recommender Systems, RecSys 2025 |
|---|---|
| Country/Territory | Czech Republic |
| City | Prague |
| Period | 9/22/25 → 9/26/25 |
Bibliographical note
Publisher Copyright:© 2025 Copyright held by the owner/author(s).
Keywords
- Context
- Context-Aware Recommendation
- Contextual Modeling
- Sequence-Aware Recommendation