Abstract
The research presented in this paper is part of an ongoing work to define semantic relatedness measures to any given semantic graph. These measures are based on a prior definition of a family of proximity algorithms that computes the semantic relatedness between pairs of concepts, and are parametrized by a semantic graph and a set of weighted properties. The distinctive feature of the proximity algorithms is that they consider all paths connecting two concepts in the semantic graph. These parameters must be tuned in order to maximize the quality of the semantic measure against a benchmark data set. From a previous work, the process of tuning the weight assignment is already developed and relies on a genetic algorithm. The weight tuning process, using all the properties in the semantic graph, was validated using WordNet 2.0 and the data set WordSim-353. The quality of the obtained semantic measure is better than those in the literature. However, this approach did not produce equally good results in larger semantic graphs such as WordNet 3.0, DBPedia and Freebase. This was in part due to the size of these graphs. The current approach is to select a sub-graph of the original semantic graph, small enough to enable processing and large enough to include all the relevant paths. This paper provides an overview of the ongoing work and presents a strategy to overcome the challenges raise by large semantic graphs.

Abstract
This workshop intends to establish the basis of a roadmap addressing engineering challenges and emerging themes in HCI. Novel forms of interaction and new application domains involve aspects that are currently not sufficiently covered by existing methods and tools. The workshop will serve as a venue to bring together researchers and practitioners interested the Engineering of Human- Computer Interaction and in contributing to the definition of a roadmap for the field. The intention is to continue work on the roadmap in follow-up workshops as well as in the IFIP Working Group on User Interface Engineering. Copyright © 2014 ACM 978-1-4503-2725-1/14/06.

Abstract
Extended Manufacturing Environments (EMEs) are nowadays growing due to the increase on Distributed and Virtual Enterprises, which led to an emergent need to apply scheduling approaches accordingly. This can be achieved in several different ways, namely by putting forward new approaches or by trying to adapt existing ones. In this paper the adaptation of some existing scheduling methods is proposed for solving a two stage manufacturing scheduling problem, and an illustrative example is presented. Several approaches were analyses, namely through the use of the ANOV A and the Post Hoc Scheffe's test, that demonstrated the superior performance of one of the proposed methods.

Abstract
Despite being a recent phenomenon and being in constant evolution, e-commerce (EC) is already embedded in current society. However, difficulties in establishing a universally accepted definition have resulted in a multiplicity of meanings that sometimes merge with the e-business (EB) concept. This article presents a brief historical and conceptual evolution of EC and some of its most significant aspects.

Abstract
In this paper a constructive heuristic for solving the staff scheduling problem of a glass manufacture unit is proposed. Based on simple calculations and algorithms, the developed procedure assigns working shifts and days-off to teams of employees, ensuring the satisfaction of a mandatory sequence of working shifts and the balance of the workload between employees. The computational times for the experiments with the case study company, with three eight-hour working shifts and five teams of employees, fell consistently below 5 seconds for a set of different planning periods. Results are compared with the ones achieved with an optimization model (MIP), demonstrating the good performance of the heuristic, also in terms of the quality of the achieved solutions. The heuristic rarely fails to produce a feasible solution and whenever the solution is feasible then it is also optimal. When tackling problems with a large number of teams, the heuristic maintains the good performance while the MIP model is not able to find any solution within 16 hours of running time. Although it was designed for a particular problem of the glass industry, tests show that the heuristic is flexible enough to be applied to problems with different features, from other activity sectors, encouraging further extensions of this work.

Abstract
Current manufacturing scheduling has still difficulties to deal with real-world situations and, hence, human intervention is required to maintain real-time adaptation and optimization, to efficiently adapt to the inherent complex system dynamics. In this paper the prototype of an Adaptive Decision Support System for Interactive Scheduling with MetaCognition and User Modeling Experience (ADSyS) is proposed. A preliminary usability evaluation was streamlined to collect user's opinion about the system performance and interaction model.