Difference between revisions of "RecSys 2019"
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Tim Holzheim (talk | contribs) (Added page provenance(#264) and contribution type(#271)) |
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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 | ||
+ | |Submitted papers=354 | ||
+ | |Accepted papers=76 | ||
+ | |pageCreator=Saskia.Ernert | ||
+ | |pageEditor=Britta.Seeberg | ||
+ | |contributionType=1 | ||
}} | }} | ||
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 | ||
Line 20: | Line 25: | ||
* Algorithm scalability, performance, and implementations | * Algorithm scalability, performance, and implementations | ||
* Bias, bubbles and ethics of recommender systems | * 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 |
Latest revision as of 19:59, 1 April 2022
RecSys 2019 | |
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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: | Copenhagen, Denmark |
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