Recently, there has been growing interest in recommender systems (RS) and particularly in context-aware RS. Methods for generating context-aware recommendations are classified into pre-filtering, post-filtering and contextual modelling approaches. In this paper, we present the several novel approaches of the different variant of each of these three contextualization paradigms and present a complete survey on the state-of-the-art comparisons across them. We then identify the significant challenges that require being addressed by the current RS researchers, which will help academicians and practitioners in comparing these three approaches to select the best alternative according to their strategies
Context-aware recommender systems (CARSs) gradually play a crucial role in modern information system...
network-based architecture recommendatio; context-aware recommendation. Abstract. The traditional re...
In this paper, we give an overview of our work to investigate the integration of context into differ...
In this thesis context-aware recommender model is created and evaluated. In the first part of the pa...
The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-39878-0_13Pro...
Traditional recommendation systems utilise past users’ preferences to predict unknown ratings and re...
Intelligent data handling techniques are beneficial for users; to store, process, analyze and access...
Several research works have demonstrated that if users' ratings are truly context-dependent, then Co...
Recommender systems are systems that provide recommendations to a user based on information gathered...
Context-aware recommender systems (CARS) generate more relevant recommendations by adapting them to...
Context Aware Recommender Systems (CARS) have become an important research area since its introducti...
Abstract. During the last decade, several recommendation systems have been proposed that help people...
In the world of Big Data, a tool capable of filtering data and providing choice support is crucial. ...
Recommender systems are software tools and techniques providing suggestions and recommendations for ...
The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-40643-0_5Proc...
Context-aware recommender systems (CARSs) gradually play a crucial role in modern information system...
network-based architecture recommendatio; context-aware recommendation. Abstract. The traditional re...
In this paper, we give an overview of our work to investigate the integration of context into differ...
In this thesis context-aware recommender model is created and evaluated. In the first part of the pa...
The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-39878-0_13Pro...
Traditional recommendation systems utilise past users’ preferences to predict unknown ratings and re...
Intelligent data handling techniques are beneficial for users; to store, process, analyze and access...
Several research works have demonstrated that if users' ratings are truly context-dependent, then Co...
Recommender systems are systems that provide recommendations to a user based on information gathered...
Context-aware recommender systems (CARS) generate more relevant recommendations by adapting them to...
Context Aware Recommender Systems (CARS) have become an important research area since its introducti...
Abstract. During the last decade, several recommendation systems have been proposed that help people...
In the world of Big Data, a tool capable of filtering data and providing choice support is crucial. ...
Recommender systems are software tools and techniques providing suggestions and recommendations for ...
The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-40643-0_5Proc...
Context-aware recommender systems (CARSs) gradually play a crucial role in modern information system...
network-based architecture recommendatio; context-aware recommendation. Abstract. The traditional re...
In this paper, we give an overview of our work to investigate the integration of context into differ...