Architecture for Context-Aware Pro-Active Recommender System
Hend Al Tair, Mohamed Jamal Zemerly, Mahmoud Al‐Qutayri, Marcello Leida · International Journal of Multimedia and Image Processing · 2012
This paper presents architecture of a contextaware pro-active recommender system.The system uses contextual information in order to provide recommendations that are more suitable to the particular individual user.Reduction-based theory has been used in order to be able to use the contextual information besides the user and item components of traditional two dimensional recommender systems.The proposed recommender system provides recommendations pro-actively by using multi-agent technology.The inference engine of the system uses conditional probability and multiattribute theory in the decision making of what recommendations to be provided to users.