Difference between revisions of "RecSys 2018"
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{{Event | {{Event | ||
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|Submission deadline=2018/05/07 | |Submission deadline=2018/05/07 | ||
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|Abstract deadline=2018/04/30 | |Abstract deadline=2018/04/30 | ||
|Paper deadline=2018/05/07 | |Paper deadline=2018/05/07 | ||
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|has general chair=Sole Pera, Michael Ekstrand | |has general chair=Sole Pera, Michael Ekstrand | ||
|has program chair=Xavier Amatriain, John O’Donovan | |has program chair=Xavier Amatriain, John O’Donovan | ||
| − | | | + | |Acronym =RecSys 2018 |
| − | | | + | |End date =2018/10/07 |
| − | |State=CA/BC}} | + | |Series =RecSys |
| + | |Type =Conference | ||
| + | |Country =CA | ||
| + | |State =CA/BC | ||
| + | |City =CA/BC/Vancouver | ||
| + | |Homepage =https://recsys.acm.org/recsys18/ | ||
| + | |Start date =2018/10/02 | ||
| + | |Title =12th ACM Conference on Recommender Systems | ||
| + | |Accepted papers =81 | ||
| + | |Submitted papers =331}} | ||
Topics of interest for RecSys 2018 include (but are not limited to): | Topics of interest for RecSys 2018 include (but are not limited to): | ||
Revision as of 21:02, 3 November 2021
Event Rating
| median | worst |
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List of all ratings can be found at RecSys 2018/rating
| 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: | CA/BC/Vancouver, CA/BC, CA |
| Important dates | |
| Abstracts: | 2018/04/30 |
| Papers: | 2018/05/07 |
| Submissions: | 2018/05/07 |
| Camera ready due: | 2018/08/06 |
| 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