@ARTICLE{10.21494/ISTE.OP.2020.0584, 

TITLE={Context aware recommender systems - toward a context typology}, 
  
AUTHOR={Elsa Negre, }, 
	
JOURNAL={Open Journal in Information Systems Engineering}, 
	
VOLUME={1}, 

NUMBER={Issue 4}, 
	
YEAR={2020}, 

URL={http://openscience.fr/Context-aware-recommender-systems-toward-a-context-typology}, 
	
DOI={10.21494/ISTE.OP.2020.0584}, 
	
ISSN={2634-1468}, 
	
ABSTRACT={The rise in volume of data and information from various sources requires effective information/data filtering to be closer to the user and best meet his/her needs. For this purpose, context-aware recommender systems that take into account the context of the user in their recommendation process, have been proposed. However, there is still no unique definition for context. In this article, we propose a typology of the user context for (context-aware) recommender systems,
in order to overcome the shortcomings of the previous proposals and to answer a rather wide spectrum of application cases. Indeed, this typology is generic with great applicability. We also show how to use it, either in the phase of gathering contextual information, the modeling or the integration within a context-aware recommender system.}}