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Researcher
Simon Dooms
- Disciplines:Machine learning and decision making, Parallel programming, Human-computer interaction
Affiliations
- Department of Information technology (Department)
Member
From10 Jul 2009 → 20 Sep 2015
Projects
1 - 1 of 1
- Dynamically generated personalized and optimal hybrid recommender systemsFrom1 Oct 2010 → 5 Jan 2016Funding: IWT personal funding - specialisation scholarships
Publications
1 - 10 of 31
- A framework for dataset benchmarking and its application to a new movie rating dataset(2016)
Authors: Simon Dooms, Alejandro Bellogin, Toon De Pessemier, Luc Martens
- Online optimization for user-specific hybrid recommender systems(2015)
Authors: Simon Dooms, Toon De Pessemier, Luc Martens
Pages: 11297 - 11329 - Offline optimization for user-specific hybrid recommender systems(2015)
Authors: Simon Dooms, Toon De Pessemier, Luc Martens
Pages: 3053 - 3076 - Recommender systems challenge 2014(2014)
Authors: Alan Said, Simon Dooms, Babak Loni, Domonkos Tikk
Pages: 387 - 388 - Mining cross-domain rating datasets from structured data on Twitter(2014)
Authors: Simon Dooms, Toon De Pessemier, Luc Martens
Pages: 621 - 624 - Comparison of group recommendation algorithms(2014)
Authors: Toon De Pessemier, Simon Dooms, Luc Martens
Pages: 2497 - 2541 - Context-aware recommendations through context and activity recognition in a mobile environment(2014)
Authors: Toon De Pessemier, Simon Dooms, Luc Martens
Pages: 2925 - 2948 - Dynamic generation of personalized hybrid recommender systems(2014)
Authors: Simon Dooms
- In-memory, distributed content-based recommender system(2014)
Authors: Simon Dooms, Jan Fostier, Toon De Pessemier, Luc Martens
Pages: 645 - 669 - Improving IMDb movie recommendations with interactive settings and filters(2014)Volume: 1247
Authors: Simon Dooms, Toon De Pessemier, Luc Martens
Number of pages: 1