Difference between revisions of "RecSys 2019"
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{{Event | {{Event | ||
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|Submission deadline=2019/04/23 | |Submission deadline=2019/04/23 | ||
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|Abstract deadline=2019/04/15 | |Abstract deadline=2019/04/15 | ||
|Paper deadline=2019/04/23 | |Paper deadline=2019/04/23 | ||
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|has general chair=Toine Bogers, Alain Said | |has general chair=Toine Bogers, Alain Said | ||
|has program chair=Domonkos Tikk, Peter Brusilovsky | |has program chair=Domonkos Tikk, Peter Brusilovsky | ||
− | | | + | |Acronym =RecSys 2019 |
− | | | + | |End date =2019/09/20 |
− | |State=US/NY}} | + | |Series =RecSys |
+ | |Type =Conference | ||
+ | |Country =US | ||
+ | |State =US/NY | ||
+ | |City =US/NY/Copenhagen | ||
+ | |Homepage =https://recsys.acm.org/recsys19/ | ||
+ | |Start date =2019/09/16 | ||
+ | |Title =13th ACM Conference on Recommender Systems | ||
+ | |Accepted papers =76 | ||
+ | |Submitted papers =354}} | ||
Topics of interest for RecSys 2019 include but are not limited to (alphabetically ordered | Topics of interest for RecSys 2019 include but are not limited to (alphabetically ordered | ||
Revision as of 02:44, 25 October 2021
Event Rating
median | worst |
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List of all ratings can be found at RecSys 2019/rating
RecSys 2019 | |
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13th ACM Conference on Recommender Systems
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Event in series | RecSys |
Dates | 2019/09/16 (iCal) - 2019/09/20 |
Homepage: | https://recsys.acm.org/recsys19/ |
Location | |
Location: | US/NY/Copenhagen, US/NY, US |
Important dates | |
Abstracts: | 2019/04/15 |
Papers: | 2019/04/23 |
Submissions: | 2019/04/23 |
Camera ready due: | 2019/07/22 |
Papers: | Submitted 354 / Accepted 76 (21.5 %) |
Committees | |
General chairs: | Toine Bogers, Alain Said |
PC chairs: | Domonkos Tikk, Peter Brusilovsky |
Table of Contents | |
Topics of interest for RecSys 2019 include but are not limited to (alphabetically ordered
- Algorithm scalability, performance, and implementations
- Bias, bubbles and ethics of recommender systems
- Case studies of real-world implementations
- Context-aware recommender systems
- Conversational recommender systems
- Cross-domain recommendation
- Economic models and consequences of recommender systems
- Evaluation metrics and studies
- Explanations and evidence
- Innovative/New applications
- Interfaces for recommender systems
- Novel machine learning approaches to recommendation algorithms (deep learning, reinforcement learning, etc.)
- Preference elicitation
- Privacy and Security
- Social recommenders
- User modelling
- Voice, VR, and other novel interaction paradigms