Information management in work organization domain in network organizations

Tese de mestrado. Engenharia Electrotécnica e de Computadores. Faculdade de Engenharia. Universidade do Porto. 200

An Ontology Centric Architecture For Mediating Interactions In Semantic Web-Based E-Commerce Environments

Information freely generated, widely distributed and openly interpreted is a rich source of creative energy in the digital age that we live in. As we move further into this irrevocable relationship with self-growing and actively proliferating information spaces, we are also finding ourselves overwhelmed, disheartened and powerless in the presence of so much information. We are at a point where, without domain familiarity or expert guidance, sifting through the copious volumes of information to find relevance quickly turns into a mundane task often requiring enormous patience. The realization of accomplishment soon turns into a matter of extensive cognitive load, serendipity or just plain luck. This dissertation describes a theoretical framework to analyze user interactions based on mental representations in a medium where the nature of the problem-solving task emphasizes the interaction between internal task representation and the external problem domain. The framework is established by relating to work in behavioral science, sociology, cognitive science and knowledge engineering, particularly Herbert Simon’s (1957; 1989) notion of satisficing on bounded rationality and Schön’s (1983) reflective model. Mental representations mediate situated actions in our constrained digital environment and provide the opportunity for completing a task. Since assistive aids to guide situated actions reduce complexity in the task environment (Vessey 1991; Pirolli et al. 1999), the framework is used as the foundation for developing mediating structures to express the internal, external and mental representations. Interaction aids superimposed on mediating structures that model thought and action will help to guide the “perpetual novice” (Borgman 1996) through the vast digital information spaces by orchestrating better cognitive fit between the task environment and the task solution. This dissertation presents an ontology centric architecture for mediating interactions is presented in a semantic web based e-commerce environment. The Design Science approach is applied for this purpose. The potential of the framework is illustrated as a functional model by using it to model the hierarchy of tasks in a consumer decision-making process as it applies in an e-commerce setting. Ontologies are used to express the perceptual operations on the external task environment, the intuitive operations on the internal task representation, and the constraint satisfaction and situated actions conforming to reasoning from the cognitive fit. It is maintained that actions themselves cannot be enforced, but when the meaning from mental imagery and the task environment are brought into coordination, it leads to situated actions that change the present situation into one closer to what is desired. To test the usability of the ontologies we use the Web Ontology Language (OWL) to express the semantics of the three representations. We also use OWL to validate the knowledge representations and to make rule-based logical inferences on the ontological semantics. An e-commerce application was also developed to show how effective guidance can be provided by constructing semantically rich target pages from the knowledge manifested in the ontologies

An expert system for safety instrumented system in petroleum industry

The expert system technology has been developed since 1960s and now it has proven to be a useful and effective tool in many areas. It helps shorten the time required to accomplish a certain job and relieve the workload for human staves by implement the task automatically. This master thesis gives general introduction about the expert system and the technologies involved with it. We also discussed the framework of the expert system and how it will interact with the existing cause and effect matrix. The thesis describes a way of implementing automatic textual verification and the possibility of automatic information extraction in the designing process of safety instrumented systems. We use the Protégé application [*] to make models for the Cause and Effect Matrix and use XMLUnit to implement the comparison between two files of interest

ICE-B 2010:proceedings of the International Conference on e-Business

The International Conference on e-Business, ICE-B 2010, aims at bringing together researchers and practitioners who are interested in e-Business technology and its current applications. The mentioned technology relates not only to more low-level technological issues, such as technology platforms and web services, but also to some higher-level issues, such as context awareness and enterprise models, and also the peculiarities of different possible applications of such technology. These are all areas of theoretical and practical importance within the broad scope of e-Business, whose growing importance can be seen from the increasing interest of the IT research community. The areas of the current conference are: (i) e-Business applications; (ii) Enterprise engineering; (iii) Mobility; (iv) Business collaboration and e-Services; (v) Technology platforms. Contributions vary from research-driven to being more practical oriented, reflecting innovative results in the mentioned areas. ICE-B 2010 received 66 submissions, of which 9% were accepted as full papers. Additionally, 27% were presented as short papers and 17% as posters. All papers presented at the conference venue were included in the SciTePress Digital Library. Revised best papers are published by Springer-Verlag in a CCIS Series book

Design and implementation of an autonomous, proactive, and reactive software infrastructure to help improving the management level of projects

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e de ComputadoresOver the years, collaboration between humans and organizations have been increasing and becoming vital to face new challenges and achieve the greatest common goals. The development of new technologies and internet capabilities promoted the emergence of new collaboration types, i.e., collaboration using software connected through internet (Collaborative Workspaces software). The use of the internet amplifies the range of action and the speed of communication among the actors involved in a collaboration. The collaboration amongst organizations is project-oriented (the common goal is to deal with projects) where several actors involved in the collaboration share their knowledge with each other. These actors are, indeed, the knowledge holders and the system which supports the collaboration has to collect and assess the knowledge from them. For this reason, this thesis aims to design and implement a software infrastructure to capture and capitalize the knowledge created over several projects. Such software is human-centered and has an autonomous, proactive and reactive behaviour to handle all users‟ needs. This software promotes its own continuous learning by analysing humans‟ behaviour over several projects, extracting information from that behaviour, and having Context-awareness. Additionally, it relies on Data mining technologies and semantic services, in order to provide a continuous monitoring of the whole project during its life cycle. The software developed is called “Companion” and has been assessed as a part of the CoSpaces Integrated Project

Development of an Ontology of Tourist Attractions for Recommending Points of Interest in a Group Recommender System for Tourism

In recent years, the tourism industry has witnessed substantial growth, thanks to the pro liferation of digital technology and online platforms. Tourists now have greater access to information and the ability to make informed travel decisions. However, the abundance of available information often leaves tourists overwhelmed when selecting points of inter est (POI) that align with their preferences. Recommender Systems (RS) have emerged as a solution, personalising recommendations based on tourist behaviour, social networks, and contextual factors. To enhance RS efficacy, researchers have begun exploring the integration of psychological factors, such as personality traits. Yet, to meet the demands of modern tourists, a robust knowledge base, such as a tourist attractions ontology, is essential for seamless and rapid matching of tourist characteristics and preferences with available POI. With that in mind, this project aims to enhance a Group Recommender System (GRS) prototype, GrouPlanner, by creating a robust tourist attractions ontology. This ontology will facilitate rapid and accurate matching of points of interest with tourists’ character istics, including personality, preferences, and demographic data, ultimately improving POI recommendations. First, there needs to be an understanding of the personality of tourists and how it influences their choices when it comes to picking the best point of interest based on their personality. With that knowledge acquired, it is time to choose a way to represent this knowledge in the form of an ontology. In this project, the Protégé ontology editor was used to design the ontology and the rela tionships between the tourists’ personality and the points of interest. After designing the ontology, it had to be converted to a database so the Grouplanner system could access it. So, to do that, a solution was designed to integrate the designed ontology in a triple store data base, in this case, Apache Fuseki. With the database implemented, several tests were made to verify if the database would give the recommended points of interests based on the tourists’ preferences. This tests were later analysed.Nos anos mais recentes, a indústria do turismo presenciou um crescimento substancial dev ido à tecnologia digital e plataformas online. Cada vez mais, os turistas têm acesso a uma abundância de informação que influencia a habilidade de tomar decisões sobre viajar. No entanto, esta informação pode complicar a seleção dos pontos de interesse que alinhem com as preferências dos turistas. Para combater isso, sistemas de recomendação (SR) emergi ram como uma solução, personalizando as recomendações com base no comportamento do turista, redes socias e outros fatores. Para aumentar a eficácia destes sistemas, os investi gadores começaram a explorar a possibilidade de integração com fatores psicológicos, como traços de personalidade. Apesar disso, para cumprir as exigências dos turistas modernos, uma base de conhecimento robusta, como uma ontologia de atrações turísticas, é essencial para, de forma eficaz e eficiente, corresponder as características dos turistas com os pontos de interesse disponíveis. Com isso em mente, este projeto tem como objetivo melhorar um protótipo de um sistema de recomendação (GrouPlanner), criando uma ontologia robusta de atrações turísticas. Essa ontologia facilitará a correspondência rápida e precisa de pontos de interesse com as car acterísticas dos turistas, incluindo a sua personalidade e as suas preferências, melhorando assim as recomendações de pontos de interesse. Em primeiro lugar, é necessário compreender a personalidade dos turistas e como ela influ encia as suas escolhas ao selecionar o melhor ponto de interesse com base na sua person alidade. Com esse ponto adquirido, é necessário escolher uma maneira de representar esse conhecimento na forma de uma ontologia. Neste projeto, o editor de ontologias Protégé foi utilizado para projetar a ontologia e as relações entre a personalidade dos turistas e os pontos de interesse. Após a construção da ontologia, foi necessário convertê-la numa base de dados para que o sistema Grouplanner pudesse ter acesso. Para isso, foi desenhada uma solução para integrar a ontologia projetada numa base de dados "triple store", neste caso, o Apache Fuseki. Com a base de dados implementada, foram realizados vários testes para verificar se esta forneceria os pontos de interesse recomendados com base nas preferências dos turistas. Esses testes foram depois analisados

Experimental Evaluation of Growing and Pruning Hyper Basis Function Neural Networks Trained with Extended Information Filter

In this paper we test Extended Information Filter (EIF) for sequential training of Hyper Basis Function Neural Networks with growing and pruning ability (HBF-GP). The HBF neuron allows different scaling of input dimensions to provide better generalization property when dealing with complex nonlinear problems in engineering practice. The main intuition behind HBF is in generalization of Gaussian type of neuron that applies Mahalanobis-like distance as a distance metrics between input training sample and prototype vector. We exploit concept of neuron’s significance and allow growing and pruning of HBF neurons during sequential learning process. From engineer’s perspective, EIF is attractive for training of neural networks because it allows a designer to have scarce initial knowledge of the system/problem. Extensive experimental study shows that HBF neural network trained with EIF achieves same prediction error and compactness of network topology when compared to EKF, but without the need to know initial state uncertainty, which is its main advantage over EKF

Bioinspired metaheuristic algorithms for global optimization

This paper presents concise comparison study of newly developed bioinspired algorithms for global optimization problems. Three different metaheuristic techniques, namely Accelerated Particle Swarm Optimization (APSO), Firefly Algorithm (FA), and Grey Wolf Optimizer (GWO) are investigated and implemented in Matlab environment. These methods are compared on four unimodal and multimodal nonlinear functions in order to find global optimum values. Computational results indicate that GWO outperforms other intelligent techniques, and that all aforementioned algorithms can be successfully used for optimization of continuous functions

From collaborative virtual research environment SOA to teaching and learning environment SOA

This paper explores the extension of the CORE VRE SOA to a collaborative virtual teaching and learning environment (CVTLE) SOA. Key points are brought up to date from a number of projects researching and developing a CVTLE and its component services. Issues remain: there are few implementations of the key services needed to demonstrate the CVTLE concept; there are questions about the feasibility of such an enterprise; there are overlapping standards; questions about the source and use of user profile data remain difficult to answer; as does the issue of where and how to coordinate, control, and monitor such a teaching and learning syste