A Context-Awareness Based Personalized Recommender System in a Pervasive Application Space

Abstract

In this paper, we propose a context-awareness based personalized recommender system in the pervasive application space. The recommender system comprises the personalized recommender engine and the distributed context management framework. With a hybrid approach, the personalized recommender engine combines those contexts into the decisions on recommendations to get more comprehensive recommendation effectiveness. In contrast with existing middleware of context-awareness, the recommender system has an ability of user-centric recommendation. At the end of this paper, an emphasis is put on the metrics of the effectiveness of the recommender system.