A switching multi-level method for the long tail recommendation problem

Author:

Alshammari Gharbi1,Jorro-Aragoneses Jose L.2,Polatidis Nikolaos1,Kapetanakis Stelios1,Pimenidis Elias3,Petridis Miltos4

Affiliation:

1. School of Computing, Engineering and Mathematics, University of Brighton, Brighton, United Kingdom

2. Department of Software Engineering and Artificial Intelligence, Complutense University, Madrid, Spain

3. Department of Computer Science and Creative Technologies, University of the West of England, Bristol, United Kingdom

4. Department of Computer Science, Middlesex University, London, United Kingdom

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

Reference28 articles.

1. Alshammari G. , Jorro-Aragoneses J.L. , Polatidis N. , Kapetanakis S. and Petridis M. , A switching approach that improves prediction accuracy for long tail recommendations, Intelligent System Conference, (2019). (in press).

2. Grouplens: An open architecture for collaborative filtering of netnews, In;Resnick;Proceedings of the 1994 ACM Conference on Computer Supported Cooperative Work,1994

3. Recommending based on rating frequencies: Accurate enough? In;Gedikli;Proceedings of the 8th Workshop on Intelligent Techniques for Web Personalization & Recommender Systems at UMAP’10 (ITWP’10),2010

4. Improving memory-based collaborative filtering via similarity updating and prediction modulation;Jeong;Information Sciences,2010

5. Recommender systems: From algorithms to user experience;Konstan;User Modeling and Useradapted Interaction,2012

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