Mobile application to provide personalized sightseeing tours

Tourist recommendation systems have been growing over the last years, mainly because of the use of mobile devices to get user context. This work discuss some of the most relevant systems on the field and presents PSiS Mobile, which is a mobile recommendation and planning application designed to support a tourist during his vacations. It provides recommendations about points of interest to visit based on tourist preferences and on user and sight context. Also, it suggests a visit planning which can be dynamically adapted based on current user and sight context. This tool works like a journey dairy since it records the tourist moves and tasks to help him remember how the trip was like. To conclude, some field experiences will be presented.

Interoperability on e-learning 2.0: the PEACE case study

The confluence of education with the evolution of technology boosted the paradigm shift of the face-to-face learning to distance learning. In this scenario e-Learning plays an essential role as a facilitator of the teaching/learning process. However new demands associated with the new Web paradigm require that existent e-Learning environments characterized mostly by monolithic systems begin interacting with new specialized services. In this decentralized scenario the definition of a strategy of interoperability is the cornerstone to ensure the standardization communication among systems. This paper presents a definition of an interoperability strategy for an e-Learning environment at our School (ESEIG) called PEACE – Project for ESEIG Academic Content Environment. This new interoperability model relies on the application of several coordination and integration standards on several services, controlled by teachers and students, and included in the PEACE environment such as social networks, repositories, libraries, e-portfolios, intelligent tutors, recommendation systems and virtual classrooms.

A hybrid recommendation approach for a tourism system

Many current e-commerce systems provide personalization when their content is shown to users. In this sense, recommender systems make personalized suggestions and provide information of items available in the system. Nowadays, there is a vast amount of methods, including data mining techniques that can be employed for personalization in recommender systems. However, these methods are still quite vulnerable to some limitations and shortcomings related to recommender environment. In order to deal with some of them, in this work we implement a recommendation methodology in a recommender system for tourism, where classification based on association is applied. Classification based on association methods, also named associative classification methods, consist of an alternative data mining technique, which combines concepts from classification and association in order to allow association rules to be employed in a prediction context. The proposed methodology was evaluated in some case studies, where we could verify that it is able to shorten limitations presented in recommender systems and to enhance recommendation quality.

Integration of repositories in elearning systems

The wide acceptance of digital repositories today in the eLearning field raises several interoperability issues. In this paper we present the interoperability features of a service oriented repository of learning objects called crimsonHex. These features are compliant with the existing standards and we propose extensions to the IMS interoperability recommendation, adding new functions, formalizing message interchange and providing also a REST interface. To validate the proposed extensions and its implementation in crimsonHex we developed a repository plugin for Moodle 2.0 that is expected to be included in the next release of this popular learning management system.