Recommender Systems depend fundamentally on user feedback to provide recommendation. Classical Recom-menders are based only historical data and also suffer from several problems linked the lack of such as sparsity. Users’ reviews represent a massive amount valuable rich knowledge information, but they still ignored by most current recommender systems. Information users’ preferences contextual c...

The evaluation and selection of recommender systems is a difficult decision making process. This difficulty is partially due to the large diversity of published evaluation criteria in addition to lack of standardized methods of evaluation. As such, a systematic methodology is needed that explicitly considers multiple, possibly conflicting metrics and assists decision makers to evaluate and find...

Context-aware systems enable the sensing and analysis of user context in order to provide personalized services to users. We observed that it is possible to automatically learn contextual factors and behavioral patterns when users interact with the system. We later utilize the learned patterns to infer contextual user interests within a recommender system. We present a novel context-aware model...

The Fourth International Conference on Context-Aware Systems and Applications (ICCASA 2015) [1] is jointly organized by EAI, Nguyen Tat Thanh University (NTTU), and Ba Ria-Vung Tau University (BRVTU) and endorsed by the European Alliance for Innovation (EAI), a leading community-based organization devoted to the advancement of innovation in the field of ICT. The event consists of a main track o...

Social network sites have attracted millions of users with the social revolution in Web 2.0. In the social network sites, a user can register other users as friends and enjoy communication. However, users of social network sites may easily get overwhelmed by the excessive volume of friend information. Recently context-aware mobile devices have been thoroughly integrated into all walks of life. ...

This paper presents a semantic recommender method and a system for a personalized access to digital cultural heritage through context-aware user profiling. Given annotation knowledge-bases, explicit background knowledge in the form of ontologies, a user model capturing the user’s behavior and context, the system produces recommendations. Ontology-based user profiling can be used to reduce cold-...

This paper presents a recommender system for N-screen services in which users have multiple devices with different capabilities. In N-screen services, a user can use various devices in different locations and time and can change a device while the service is running. N-screen aware recommendation seeks to improve the user experience with recommended content by considering the user N-screen devi...

A context-aware system is a system that uses context to provide relevant information or services to its users. While there has been a variety of context middleware infrastructures and context-aware applications, little work has been done on integrating context into database management systems. In this paper, we consider a preference database system that supports context-aware queries, that is, ...