Difference between revisions of "RecSys 2019"
		
		
		
		
		
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|has program chair=Domonkos Tikk, Peter Brusilovsky  | |has program chair=Domonkos Tikk, Peter Brusilovsky  | ||
|Acronym          =RecSys 2019  | |Acronym          =RecSys 2019  | ||
| − | |End date         =2019  | + | |End date         =2019-09-20  | 
|Series           =RecSys  | |Series           =RecSys  | ||
|Type             =Conference  | |Type             =Conference  | ||
| Line 13: | Line 13: | ||
|State            =US/NY  | |State            =US/NY  | ||
|City             =US/NY/Copenhagen  | |City             =US/NY/Copenhagen  | ||
| + | |Year             =2019  | ||
|Homepage         =https://recsys.acm.org/recsys19/  | |Homepage         =https://recsys.acm.org/recsys19/  | ||
| − | |Start date       =2019  | + | |Start date       =2019-09-16  | 
|Title            =13th ACM Conference on Recommender Systems  | |Title            =13th ACM Conference on Recommender Systems  | ||
|Accepted papers  =76  | |Accepted papers  =76  | ||
| − | |Submitted papers =354}}  | + | |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  | ||
Latest revision as of 03:14, 6 December 2021
Event Rating
| median | worst | 
|---|---|
List of all ratings can be found at RecSys 2019/rating
| RecSys 2019 | |
|---|---|
13th ACM Conference on Recommender Systems 
 | |
| 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