< Back to previous page


Dynamically generated personalized and optimal hybrid recommender systems

The goal of the project is to research strategies to combine modern recommendation algorithms in a dynamic and personalized way. Doing so will enable the generation of flexible and optimized hybrid recommendation systems tailored towards individual users and applicable in a wide range of domains.

Date:1 Oct 2010 →  5 Jan 2016
Keywords:optimalization, recommender systems, algorithms
Disciplines:Artificial intelligence, Cognitive science and intelligent systems, Visual computing, Programming languages, Information sciences, Other information and computing sciences, Scientific computing, Theoretical computer science, Computer architecture and networks, Distributed computing, Applied mathematics in specific fields, Information systems