Journal's Facebook pageDevelopment of Recommendation Systems Using Game Theoretic Techniques
- Department of Computer Engineering and Informatics, University of Patras,
Rio 26500, Patras, Greece
sofikitis@ceid.upatras.gr - Department of Computer Engineering and Informatics, University of Patras,
Rio 26500, Patras, Greece
makri@ceid.upatras.gr
Abstract
In the present work, we inquire the use of game theoretic techniques for the development of recommender systems. Initially, the interaction of the two as-pects of the systems, query reformulation and relevance estimation, is modelled as a cooperative game where the two players have a common utility, to supply optimal recommendations, which they try to maximize. Based on this modelling, three basic recommendation methods are developed, namely collaborative filtering, content based filtering and demographic filtering. The different methods are then combined to create hybrid systems. In the weighted combination, the use of game theoretic techniques is extended, as it is modelled as a cooperative game. Finally, the methods are combined with the use of a genetic algorithm where game theory is used for the parent selection process. Our work offers a baseline for the efficient combination of recommendation methods through game theory and in addition the novelty method, Choice by Game, for the parent selection process in genetic algorithms which offers consistent performance improvements.
Key words
recommendation system, game theory, genetic algorithm
Digital Object Identifier (DOI)
https://doi.org/10.2298/CSIS210925018S
Publication information
Volume 19, Issue 3 (September 2022)
Year of Publication: 2022
ISSN: 2406-1018 (Online)
Publisher: ComSIS Consortium
Full text
Available in PDF
Portable Document Format
How to cite
Sofikitis, E., Makris, C.: Development of Recommendation Systems Using Game Theoretic Techniques. Computer Science and Information Systems, Vol. 19, No. 3, 1133-1154. (2022), https://doi.org/10.2298/CSIS210925018S
