Difference between revisions of "RecSys 2018"

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{{Event
 
{{Event
|Acronym=RecSys 2018
 
|Title=12th ACM Conference on Recommender Systems
 
|Series=RecSys
 
|Type=Conference
 
|Start date=2018/10/02
 
|End date=2018/10/07
 
 
|Submission deadline=2018/05/07
 
|Submission deadline=2018/05/07
|Homepage=https://recsys.acm.org/recsys18/
 
|City=Vancouver
 
|Country=Canada
 
 
|Abstract deadline=2018/04/30
 
|Abstract deadline=2018/04/30
 
|Paper deadline=2018/05/07
 
|Paper deadline=2018/05/07
Line 15: Line 6:
 
|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
|Submitted papers=331
+
|Acronym          =RecSys 2018
|Accepted papers=81
+
|End date        =2018-10-07
|State=CA/BC}}
+
|Series          =RecSys
 +
|Type            =Conference
 +
|Country          =CA
 +
|State           =CA/BC
 +
|City            =CA/BC/Vancouver
 +
|Year            =2018
 +
|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):
  

Latest revision as of 04:10, 6 December 2021


Event Rating

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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
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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