Combining Situation and Content Similarities in Fuzzy Based Interest Matchmaking Mechanism

Author

Djaghloul, Y. ; Groues, V. ; Naudet, Yannick

Author_Institution

CRP Henri Tudor, Esch-sur-Alzette, Luxembourg

fYear

2012

fDate

3-4 Dec. 2012

Firstpage

9

Lastpage

14

Abstract

In this paper, we present an approach to weight the influence of context regarding user interests in content-based recommendations. The balance between interest-content matching and situation matching is formalized using a Fuzzy model, allowing more intuitive personalization. Using content consumption history, this model can be optimized from an initial general model to a new one fitting better the preferences of the user. We propose a generic service for such personalized context-aware recommendations. Experimental results are discussed and show the effectiveness comparing to a classical weighted function.

Keywords

content management; fuzzy set theory; pattern matching; recommender systems; ubiquitous computing; content consumption history; content similarity; content-based recommendation; fuzzy based interest matchmaking mechanism; fuzzy model; interest-content matching; personalization; personalized context-aware recommendation; situation matching; situation similarity; user interest; Context; Fuzzy logic; Load modeling; Ontologies; Optimization; Pragmatics; Recommender systems; Fuzzy logic; Personalization; Recommender System; Situation;

fLanguage

English

Publisher

ieee

Conference_Titel

Semantic and Social Media Adaptation and Personalization (SMAP), 2012 Seventh International Workshop on

Conference_Location

Luxembourg

Print_ISBN

978-1-4673-4563-7

Type

conf

DOI

10.1109/SMAP.2012.21

Filename

6406842