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The wide development of mobile applications provides a considerable amount of data of all types (images, texts, sounds, videos, etc.). In this sense, Mobile Context-aware Recommender Systems (MCRS) suggest the user suitable information depending on her/his situation and interests. Two key questions have to be considered 1) how to recommend the user information that follows his/her interests evolution?...
The vision of pervasive environments is being realized more than ever with the proliferation of services and computing resources located in our surrounding environments. Identifying those services that deserve the attention of the user is becoming an increasingly-challenging task. In this paper, we present an adaptive multi-criteria decision making mechanism for recommending relevant services to the...
The design of interfaces suitable for recommender and search applications on mobile devices is a complex and extensive task. Not only does one have to allow for the simple adjustment of filter settings, one also has to cope with technical and physical limitations like the reduced screen size and the lack of comfortable input methods most users are accustomed to. In this paper we consider the scenario...
This paper introduces a hybrid recommendation platform providing information about tourist resources depending on the user profile, location, schedule and the amount of time for visiting interest points isolated or combined in a route.
Recommendation Systems have become an important research area in mobile computing. Although various recommendation systems have been developed to help users to deal with information overload, few systems focus on proactive information recommendation. This paper presents a news recommender system that proactively pushes just-in-time personalized news articles to mobile users based on user's contextual...
In any systems or environments within a ubiquitous computing context that promotes the concept of users interaction or inter-organization communication, more specifically data sharing and takes users within such context as relevant contextual information, there is the potential for interactions between systems to occur that may affect the security of the overall system. We present a scenario that...
Recently, context-aware recommender systems (CARS), which incorporates contextual information into recommender systems, has become one of the hottest topics in the domain of recommender systems. In this paper, we identify and discuss some challenges for context-aware recommender systems, including viewing it as a process, valid contexts discovering and computing, contextual user preference elicitation,...
With the emergence of pervasive environment, mobile recommender needs to make use of user in-time contextual information to provide personalized recommendation. In this paper, a proactive context-aware news recommender in mobile hybrid P2P network is designed and implemented. We develop a general Analytic Hierarchy Process (AHP) model through empirical studies. We discuss how the relative weight of...
Trust is generally based on the level and quality of interaction with the entity being trusted. In a web service or the Internet, trust is based on the level of successful and unsuccessful interactions. Successful interactions are used to model trust within the context of chains of trust in which an agent is permitted to recommend a service. This is termed trust chain since the agent need to first...
Television and video consumption are growing rapidly worldwide, driving usage of second and third screens for related interactions and information. Since television has a proven impact on consumer purchase behaviors, there is commercial interest in technologies that model viewers' intent, interests and engagement. However, the ecosystem currently faces two challenges - audience fragmentation and a...
Collaborative filtering technology is the key technology of recommendation system. However, collaborative filtering technology has been suffering from sparsity that it needs mass ratings from users to improve precision. In traditional e-commerce, asking users to rate on their own initiative will degrade experience of users, let alone the mobile business environment. So, both in e-commerce and m-commerce,...
The work describes SMARTMUSEUM ICT solution of personalized cultural heritage content access for mobile users. Addressed aspects include unifying user preferences, context information and respective annotation of content. Implemented real solution is described briefly.
Users want to access user generated content and recommendations in a contextualized way while on the move. In this paper we illustrate the POI radar service and its architecture, a mobile mashup of integrated location, social network and users' recommendations to provide contextualized notifications of nearby points of interest voted by user's contacts. A description of the service scenario, architecture...
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