Abstract
Linear Meld is a concurrent forward-chaining linear logic programming language where logical facts can be asserted and retracted in a structured way. The database of facts is partitioned by the nodes of a graph structure which leads to parallelism if nodes are executed simultaneously. Communication arises whenever nodes send facts to other nodes by fact derivation. We present an overview of the virtual machine that we implemented to run Linear Meld on multicores, including code organization, thread management, rule execution and database organization for efficient fact insertion, lookup and deletion. Although our virtual machine is a work-in-progress, our results already show that Linear Meld is not only capable of scaling graph and machine learning programs but it also exhibits some interesting performance results when compared against other programming languages.

Abstract
This paper presents an approach that enables the staging of choreographies for education and training purposes in multiple virtual world platforms. Choreography is the description of a set of actions that must or may be executed by a group of participants, including the goals to be achieved and any restrictions that may exist. For capturing and representing multi-actor multidomain choreographies an approach based on ontologies with distinct levels of abstraction is adopted. Further, this paper proposes a modelling driven approach and a set of processes that, through mappings between ontologies, enable the automatic construction of a platform-specific choreography from a platform-independent one, thus reducing the time and effort of the choreography development. For this, the MDA paradigm was adopted and adapted in a way where models can reflect two dimensions of independence: platform independence and application domain independence. We also point the guidelines for staging the choreography in a virtual world platform.

Abstract
Project-based organizations (PBO) are nowadays widespread in almost all the activity sectors. This type of organizations poses complex problems for information and knowledge management due to the fragmentation and lack of uniformity of organizational structures, processes, practices, and technologies. The ineffectiveness of knowledge sharing over time, between project teams, is perhaps the most prominent issue that PBO must deal with. This strongly affects organizational learning, which seems to under-deliver value to PBO. Therefore, relevant knowledge is trapped in an "informational limbo" out of reach, not being capitalized for the organization. This is particularly true in research and development (R&D) institutions, where knowledge sharing can be hindered by conceptual misunderstandings resulting from different disciplines, cultures and ways of working of project participants. This paper addresses such issues by analyzing, in a comprehensive way, how information and knowledge management can better suit project team's needs and at the same time improve organizational learning. An ethnographic study, based on immersed participant observation, is performed at a Portuguese R&D Institute, in order to understand the link between the way information is managed in a project and how people interact and learn by sharing knowledge between projects. Results provide a set of enterprise information management (EIM) recommendations. Findings also suggest that a PBO-wide EIM strategy, balancing knowledge codification and personalization mechanisms, is a feasible solution to overcome the problems of knowledge sharing in PBO. (C) 2014 Published by Elsevier Ltd.

Abstract
Mobile devices are increasingly pervasive and are transforming information distribution paradigms. A rapidly growing segment of urban public transport passengers carry mobile computing devices, permanently and on the move. In a context of thinning financial resources, getting customers involved in the actual delivery of a public transport service as real-time information consumers and providers, may be a powerful method to enhance travel experience while reducing operational costs for the service operator. Each and every customer travelling on a public transport network has unique knowledge about the service operation as it unfolds. This paper proposes a framework that aims to unify public transport passengers' collective intelligence through crowdsourcing, using their mobile computing devices and dedicated web services. It strives to intensify win-win relationships between public transport passengers and operators. The structured exchange of information is sustained by a validation mechanism for data reliability, and an incentive mechanism to encourage passenger participation. Passengers benefit from rich real-time data tailored to their profiles, to ease their journeys and improve travel experience, in exchange for their own participation providing and validating information. Operators gain access to rich customer generated data, which in an aggregated format may provide a real-time assessment of customer experience and of local performance across the entire network operation. Operators may be required to reward travellers who become prolific co-creators of the public transport service, but higher customer experience levels, lesser needs for investment in controlling mechanisms, and continuous free monitoring of customer opinions can jointly lead to financial returns. (C) 2013 The Authors. Published by Elsevier Ltd.

Abstract
Poker is used to measure progresses in extensive-form games research due to its unique characteristics: it is a game where playing agents have to deal with incomplete information and stochastic scenarios and a large number of decision points. The development of Poker agents has seen significant advances in one-on-one matches but there are still no consistent results in multiplayer and in games against human experts. In order to allow for experts to aid the improvement of the agents' performance, we have created a high-level strategy specification language. To support strategy definition, we have also developed an intuitive graphical tool. Additionally, we have also created a strategy inferring system, based on a dynamically weighted Euclidean distance. This approach was validated through the creation of simple agents and by successfully inferring strategies from 10 human players. The created agents were able to beat previously developed mid-level agents by a good profit margin.

Abstract
Web mining can be defined as the use of data mining techniques to automatically discover and extract information from web documents and services. A decision support system is a computer-based information sy Analysis stem that supports business or organizational decision-making activities. Data mining and business intelligence techniques can be integrated in order to develop more advanced decision support systems. In this chapter, the authors propose to use web mining as a process to develop advanced decision support systems in order to support the management activities of a website. They describe the Web mining process as a sequence of steps for the development of advanced decision support systems. By following such a sequence, the authors can develop advanced decision support systems, which integrate data mining with business intelligence, for websites. © 2015, IGI Global.