Abstract
As the amount of content and the number of users in social relationships is continually growing in the Internet, resource sharing and access policy management is difficult, time-consuming and error-prone. Cross-domain recommendation of private or protected resources managed and secured by each domain’s specific access rules is impracticable due to private security policies and poor sharing mechanisms. This work focus on exploiting resource’s content, user’s preferences, users’ social networks and semantic information to cross-relate different resources through their meta information using recommendation techniques that combine collaborative-filtering techniques with semantics annotations, by generating associations between resources. The semantic similarities established between resources are used on a hybrid recommendation engine that interprets user and resources’ semantic information. The recommendation engine allows the promotion and discovery of unknownunknown resources to users that could not even know about the existence of those resources thus providing means to solve the cross-domain recommendation of private or protected resources. © Springer International Publishing AG 2016.

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Abstract
The collection of health and fitness longitudinal data can be used to model disease progression and shape new algorithms to diagnose and predict health hazards. Continuously tracking vital signs, in particular heart rate and skin temperature, can be very informative by using models and algorithms to predict and notify the user about when he might be falling ill. With the current wearable devices and the proper algorithms, the individual can be permanently monitored, which might be much more interesting than a one-off reading comparison with the population average, made by a doctor. It would be possible to intervene earlier and to prevent somebody from becoming seriously ill. From a broader perspective, the knowledge about a user’s health can be considered as an element of that user’s context and be used by context aware applications to provide higher value to the user. After the trivialization of the data acquisition sensors, wearable devices, and raw data, the next logical step is the development of contained software components that can infer and produce knowledge from the raw data. These components and the knowledge they produce can be used by all sorts of applications in order to further customize their usage by a specific user. Customization and context awareness, in regard to health, is a wide field for research and there are a multitude of proposals for models and algorithms. In this review work we searched for software components (frameworks, software libraries, etc.), freely available and that can be used as building blocks for other computer systems by software developers. Copyright

Abstract
This work explores the application of information technologies in the processes of mentoring, allowing to optimize them and adapting this service of mentoring, to the current reality. It is intended to understand the importance of e-mentoring for the improvement and achievement of objectives for both apprentices and mentors, in which it shows how the relationship between both should be done, in order to be able to communicate with knowledge sharing throughout the relationship, from its beginning to its closure.

Abstract
In an idea generation meeting, the facilitator role is essential to obtain good results. Also the emotional context of the meeting partially determines the (un) success of the meeting, being it of idea generation or decision selection. So the facilitator needs to obtain and process this information in order to assist the participants to reach their goals in different processes of decision making. In this paper is proposed a multi-agent framework able to be used in the support of persons in a affective context-aware and ubiquitous group decision process. Insights of the context-aware model are provided. It allows the gathering of certain typical variables of the affective context (emotions and mood) and transform those values in advises to the facilitator.

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