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 language | English (US) |
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Title of host publication | Proceedings of the 17th ACM Conference on Recommender Systems, RecSys 2023 |
Publisher | Association for Computing Machinery, Inc |
Pages | 1234-1236 |
Number of pages | 3 |
ISBN (Electronic) | 9798400702419 |
DOIs | |
State | Published - Sep 14 2023 |
Event | 17th ACM Conference on Recommender Systems, RecSys 2023 - Singapore, Singapore Duration: Sep 18 2023 → Sep 22 2023 |
Publication series
Name | Proceedings of the 17th ACM Conference on Recommender Systems |
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Conference
Conference | 17th ACM Conference on Recommender Systems, RecSys 2023 |
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Country/Territory | Singapore |
City | Singapore |
Period | 9/18/23 → 9/22/23 |
Bibliographical note
Publisher Copyright:© 2023 Owner/Author.
Keywords
- Context
- Context-Aware Recommendation
- Contextual Modeling
- Sequence-Aware Recommendation