ComplexRec 2017: Recommendation in Complex Scenarios

Toine Bogers (Editor), Marijn Koolen (Editor), Bamshad Mobasher (Editor), Alan Said (Editor), Alexander Tuzhilin (Editor)

Research output: Book/ReportAnthologyResearchpeer-review


Recommendation algorithms for ratings prediction and item ranking have steadily matured during the past decade. However, these state-of-the-art algorithms are typically applied in relatively straightforward scenarios. In reality, recommendation is often a more complex problem: it is usually just a single step in the user's more complex background need. These background needs can often place a variety of constraints on which recommendations are interesting to the user and when they are appropriate. However, relatively little research has been done on these complex recommendation scenarios. The ComplexRec 2017 workshop addressed this by providing an interactive venue for discussing approaches to recommendation in complex scenarios that have no simple one-size-fits-all-solution.
Original languageEnglish
PublisherCEUR Workshop Proceedings
Number of pages28
Publication statusPublished - 27 Aug 2017
EventRecSys 2017: 11th ACM Conference on Recommender Systems - Como, Italy, Como, Italy
Duration: 27 Aug 201731 Aug 2017
Conference number: 11
SeriesCEUR Workshop Proceedings


ConferenceRecSys 2017: 11th ACM Conference on Recommender Systems
LocationComo, Italy
Internet address


  • recommender systems
  • complex recommendation


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