RecSys 16 workshop on deep learning for recommender systems (DLRS)

Alexandros Karatzoglou, Balázs Hidasi, Domonkos Tikk, Oren Sar-Shalom, Haggai Roitman, Bracha Shapira

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

14 Scopus citations

Abstract

We believe that Deep Learning is one of the next big things in Recommendation Systems technology. The past few years have seen the tremendous success of deep neural networks in a number of complex tasks such as computer vision, nat- ural language processing and speech recognition. Despite this, only little work has been published on Deep Learning methods for Recommender Systems. Notable recent appli- cation areas are music recommendation, news recommenda- tion, and session-based recommendation. The aim of the workshop is to encourage the application of Deep Learning techniques in Recommender Systems, to promote research in deep learning methods for Recommender Systems, and to bring together researchers from the Recommender Systems and Deep Learning communities.

Original languageEnglish
Title of host publicationRecSys 2016 - Proceedings of the 10th ACM Conference on Recommender Systems
PublisherAssociation for Computing Machinery, Inc
Pages415-416
Number of pages2
ISBN (Electronic)9781450340359
DOIs
StatePublished - 7 Sep 2016
Event10th ACM Conference on Recommender Systems, RecSys 2016 - Boston, United States
Duration: 15 Sep 201619 Sep 2016

Publication series

NameRecSys 2016 - Proceedings of the 10th ACM Conference on Recommender Systems

Conference

Conference10th ACM Conference on Recommender Systems, RecSys 2016
Country/TerritoryUnited States
CityBoston
Period15/09/1619/09/16

Keywords

  • Deep learning
  • Neural networks
  • Recommender systems

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Hardware and Architecture
  • Computer Networks and Communications

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