Third workshop on recommendation in complex scenarios (ComplexreC 2019)

Marijn Koolen, Toine Bogers, Bamshad Mobasher, Alexander Tuzhilin

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearch


Over the past decade, recommendation algorithms for ratings prediction and item ranking have steadily matured. However, these state-of-the-art algorithms are typically applied in relatively straightforward and static scenarios: given information about a user's past item preferences in isolation, can we predict whether they will like a new item or rank all unseen items based on predicted interest? In reality, recommendation is often a more complex problem: the evaluation of a list of recommended items never takes place in a vacuum, and it is often a single step in the user's more complex background task or need. The goal of the ComplexRec 2019 workshop is to ofer an interactive venue for discussing approaches to recommendation in complex scenarios that have no simple one-size-fts-all solution.

Original languageEnglish
Title of host publicationRecSys 2019 - 13th ACM Conference on Recommender Systems
Number of pages2
PublisherAssociation for Computing Machinery
Publication date10 Sept 2019
ISBN (Electronic)9781450362436
Publication statusPublished - 10 Sept 2019
Externally publishedYes
Event13th ACM Conference on Recommender Systems, RecSys 2019 - Copenhagen, Denmark
Duration: 16 Sept 201920 Sept 2019


Conference13th ACM Conference on Recommender Systems, RecSys 2019


  • Recommendation Algorithms
  • Ratings Prediction
  • Item Ranking
  • Complex Scenarios
  • User Preferences


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