Mobile Multimedia Recommendation in Smart Communities: A Survey <s> Mobile Multimedia Recommendation in Smart <s> A mobile phone with a camera enabled people to capture moments to remember in the right time and place. Due to a limited user interface, however, a mobile phone is not yet a platform for enjoying the captured moments. We explored possible application scenarios for promoting utilization of user-created photos on a mobile phone. For the realization of the scenarios, we designed context-aware photo selection algorithms that take into consideration mobile phone contexts such as the current location and recent calls. A user study was conducted with a mobile phone prototype for the evaluation of the photo selection algorithms and also for user feedback about the photo consumption scenarios. <s> BIB001 </s> Mobile Multimedia Recommendation in Smart Communities: A Survey <s> Mobile Multimedia Recommendation in Smart <s> Mobile TV provides multimedia contents to the user by wireless communication. Here the personalized recommendation system allows the users to easily select the contents wanting to access. In this paper we propose a personalized recommendation scheme which considers the activities of the user at runtime and the information on the environment around the user. It allows efficient operation in mobile device, and interoperability between the TV multimedia metadata and ontology. The accuracy of the proposed scheme is evaluated by an experiment, which reveals a significant improvement compared to the existing schemes. <s> BIB002
Communities: A Survey recommender systems in smart communities so that the aforementioned problems and challenges in mobile multimedia can be solved, some researchers BIB002 [7]- BIB001 have investigated and developed mobile multimedia recommender systems in different smart communities. A mobile multimedia recommendation system solves the problem of multimedia overload in mobile devices by predicting and presenting relevant multimedia information to users. Users therefore don't waste appropriate time searching for contents that they are/might be interested in. The increasing interest of multimedia contents in different smart communities and the growing usage of mobile devices motivates us to conduct a detailed analysis and bring to light some important existing research work and relevant open research issues in this important scientific area. In this paper, we survey the importance and relevance of mobile multimedia recommendation systems for three smart communities, namely, mobile social learning, mobile event guides and context-aware services. Furthermore, we present an overview of mobile multimedia recommendation systems from the perspective of applications, architectures and algorithms. Through careful examination of the state-of-the-art, we outline challenges and open issues that require attention so that recommendations generated for mobile users will be more accurate, reliable, efficient and trustworthy. The rest of this paper is organized as follows. In Section II we present an overview of the smart communities. We examine the taxonomy of mobile multimedia recommender systems in Section III. Section IV reviews the existing research of mobile multimedia recommender systems for smart communities. Discussions and open issues are presented in Section V and then Section VI concludes the paper.