Abstract
Tourism crowdsourcing platforms have a profound influence on the tourist behaviour particularly in terms of travel planning. Not only they hold the opinions shared by other tourists concerning tourism resources, but, with the help of recommendation engines, are the pillar of personalised resource recommendation. However, since prospective tourists are unaware of the trustworthiness or reputation of crowd publishers, they are in fact taking a leap of faith when then rely on the crowd wisdom. In this paper, we argue that modelling publisher Trust & Reputation improves the quality of the tourism recommendations supported by crowdsourced information. Therefore, we present a tourism recommendation system which integrates: (i) user profiling using the multi-criteria ratings; (ii) k-Nearest Neighbours (k-NN) prediction of the user ratings; (iii) Trust & Reputation modelling; and (iv) incremental model update, i.e., providing near real-time recommendations. In terms of contributions, this paper provides two different Trust & Reputation approaches: (i) general reputation employing the pairwise trust values using all users; and (ii) neighbour-based reputation employing the pairwise trust values of the common neighbours. The proposed method was experimented using crowdsourced datasets from Expedia and TripAdvisor platforms. © 2018, Springer International Publishing AG, part of Springer Nature.

Abstract
This paper presents the system developed to promote the rational use of electric energy among consumers and, thus, increase the energy efficiency. The goal is to provide energy consumers with an application that displays the energy consumption/production profiles, sets up consuming ceilings, defines automatic alerts and alarms, compares anonymously consumers with identical energy usage profiles by region and predicts, in the case of non-residential installations, the expected consumption/production values. The resulting distributed system is organized in two main blocks: front-end and back-end. The front-end includes user interface applications for Android mobile devices and Web browsers. The back-end provides data storage and processing functionalities and is installed in a cloud computing platform -the Google App Engine - which provides a standard Web service interface. This option ensures interoperability, scalability and robustness to the system.

Abstract
Based on historical user information, collaborative filters predict for a given user the classification of unknown items, typically using a single criterion. However, a crowd typically rates tourism resources using multi-criteria, i.e., each user provides multiple ratings per item. In order to apply standard collaborative filtering, it is necessary to have a unique classification per user and item. This unique classification can be based on a single rating single criterion (SC) profiling or on the multiple ratings available multi criteria (MC) profiling. Exploring both SC and MC profiling, this work proposes: (iota) the selection of the most representative crowd-sourced rating; and (iota iota) the combination of the different user ratings per item, using the average of the non-null ratings or the personalised weighted average based on the user rating profile. Having employed matrix factorisation to predict unknown ratings, we argue that the personalised combination of multi-criteria item ratings improves the tourist profile and, consequently, the quality of the collaborative predictions. Thus, this paper contributes to a novel approach for guest profiling based on multi-criteria hotel ratings and to the prediction of hotel guest ratings based on the Alternating Least Squares algorithm. Our experiments with crowd-sourced Expedia and TripAdvisor data show that the proposed method improves the accuracy of the hotel rating predictions.

Abstract
Nowadays tourists rely on technology for inspiration, research, booking, experiencing and sharing. Not only it provides access to endless sources of information, but has become an unbounded source of tourist-related data. In such crowd-sourced data-intensive scenario, we argue that new approaches are required to enrich current and new travelling experiences. This work, which supports the "dreaming stage", proposes the automatic recommendation of personalised destinations based on textual reviews, i.e.,a semantic content-based filter of crowd-sourced information. Our approach relies on Topic Modelling - to extract meaningful information from textual reviews - and Semantic Similarity to identify relevant recommendations. Our main contribution is the processing of crowd-sourced tourism information employing data mining techniques in order to automatically discover untapped destinations on behalf of tourists.

Abstract
This paper proposes and reports the development of an open source solution for the integrated management of Infrastructure as a Service (IaaS) cloud computing resources, through the use of a common API taxonomy, to incorporate open source and proprietary platforms. This research included two surveys on open source IaaS platforms (OpenNebula, OpenStack and CloudStack) and a proprietary platform (Parallels Automation for Cloud Infrastructure - PACI) as well as on IaaS abstraction solutions (jClouds, Libcloud and Deltacloud), followed by a thorough comparison to determine the best approach. The adopted implementation reuses the Apache Deltacloud open source abstraction framework, which relies on the development of software driver modules to interface with different IaaS platforms, and involved the development of a new Deltacloud driver for PACI. The resulting interoperable solution successfully incorporates OpenNebula, OpenStack (reuses pre-existing drivers) and PACI (includes the developed Deltacloud PACI driver) nodes and provides a Web dashboard and a Representational State Transfer (REST) interface library. The results of the exchanged data payload and time response tests performed are presented and discussed. The conclusions show that open source abstraction tools like Deltacloud allow the modular and integrated management of IaaS platforms (open source and proprietary), introduce relevant time and negligible data overheads and, as a result, can be adopted by Small and Medium-sized Enterprise (SME) cloud providers to circumvent the vendor lock-in problem whenever service response time is not critical.

Abstract
The European Project Semester (EPS) is a one-semester capstone project/internship programme offered to engineering, product design and business undergraduates by 18 European engineering schools. EPS aims to prepare future engineers to think and act globally by adopting project-based learning and teamwork methodologies. The EPS@ISEP programme – the EPS programme provided by ISEP – the School of Engineering of the Polytechnic Institute of Porto – started in 2011 and has since welcomed 3rd and 4th year mobility students during the spring semester. In particular, sustainable development is a pervasive concern within EPS projects. It was in this context that, in 2012, a team of EPS@ISEP students decided to develop a water disinfection system. While the technical goal of the project was to design and develop a fluid disinfection system for removing bacteria, viruses and seaweeds, the overall objective was far more ambitious: to help students learn, develop and adopt sustainable practices for their future professional life. The system was intended to be a simple and effective solution for water treatment and recycling. At a larger scale, the project contributes to the preservation of the planet's fresh water resources and to the improvement of the population’s health by eliminating harmful microorganisms from the water. This challenge was, by itself, motivational and exposed the team to new learning experiences. The team found several approaches for water treatment and, after a detailed analysis, decided to adopt Ultraviolet (UV) irradiation for the removal of microorganisms. This multidisciplinary real world problem drove the team during the semester. The team surveyed and compared different methods for water cleansing and recycling, chose one approach and, then, designed, built and tested the prototype. In addition, the students also addressed marketing, sustainability as well as the ethic and deontological issues regarding the proposed solution while developing cross-cultural understanding, teamwork and communication skills. The project provided an excellent opportunity to foster the concept of sustainable development amongst students.