Difference between revisions of "RecSys 2018"
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|Accepted short papers=49 | |Accepted short papers=49 | ||
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| + | Topics of interest for RecSys 2018 include (but are not limited to): | ||
| + | |||
| + | * Conversational recommender systems | ||
| + | * Novel machine learning approaches to recommendation algorithms | ||
| + | * Evaluation metrics and studies | ||
| + | * Explanations and evidence | ||
| + | * Algorithm scalability, performance, and implementations | ||
| + | * Innovative/New applications | ||
| + | * Voice, VR, and other novel interaction paradigms | ||
| + | * Case studies of real-world implementations | ||
| + | * Preference elicitation | ||
| + | * Privacy and Security | ||
| + | * Economic models and consequences of recommender systems | ||
| + | * Personalisation | ||
| + | * Social recommenders | ||
| + | * User modelling | ||
Revision as of 16:14, 21 April 2020
| RecSys 2018 | |
|---|---|
12th ACM Conference on Recommender Systems
| |
| Event in series | RecSys |
| Dates | 2018/10/02 (iCal) - 2018/10/07 |
| Homepage: | https://recsys.acm.org/recsys18/ |
| Location | |
| Location: | Vancouver, Canada |
| Important dates | |
| Abstracts: | 2018/04/30 |
| Papers: | 2018/05/07 |
| Submissions: | 2018/05/07 |
| Camera ready due: | 2018/08/06 |
| Accepted short papers: | 49 |
| Papers: | Submitted 331 / Accepted 81 (24.5 %) |
| Committees | |
| General chairs: | Sole Pera, Michael Ekstrand |
| PC chairs: | Xavier Amatriain, John O’Donovan |
| Table of Contents | |
Topics of interest for RecSys 2018 include (but are not limited to):
- Conversational recommender systems
- Novel machine learning approaches to recommendation algorithms
- Evaluation metrics and studies
- Explanations and evidence
- Algorithm scalability, performance, and implementations
- Innovative/New applications
- Voice, VR, and other novel interaction paradigms
- Case studies of real-world implementations
- Preference elicitation
- Privacy and Security
- Economic models and consequences of recommender systems
- Personalisation
- Social recommenders
- User modelling