A Data-mining-based Methodology to support MV Electricity Customers' Characterization

This paper presents an electricity medium voltage (MV) customer characterization framework supportedby knowledge discovery in database (KDD). The main idea is to identify typical load profiles (TLP) of MVconsumers and to develop a rule set for the automatic classification of new consumers. To achieve ourgoal a methodology is proposed consisting of several steps: data pre-processing; application of severalclustering algorithms to segment the daily load profiles; selection of the best partition, corresponding tothe best consumers’ segmentation, based on the assessments of several clustering validity indices; andfinally, a classification model is built based on the resulting clusters. To validate the proposed framework,a case study which includes a real database of MV consumers is performed.

Towards a unified European electricity market: The contribution of data-mining to support realistic simulation studies

Worldwide electricity markets have been evolving into regional and even continental scales. The aim at an efficient use of renewable based generation in places where it exceeds the local needs is one of the main reasons. A reference case of this evolution is the European Electricity Market, where countries are connected, and several regional markets were created, each one grouping several countries, and supporting transactions of huge amounts of electrical energy. The continuous transformations electricity markets have been experiencing over the years create the need to use simulation platforms to support operators, regulators, and involved players for understanding and dealing with this complex environment. This paper focuses on demonstrating the advantage that real electricity markets data has for the creation of realistic simulation scenarios, which allow the study of the impacts and implications that electricity markets transformations will bring to the participant countries. A case study using MASCEM (Multi-Agent System for Competitive Electricity Markets) is presented, with a scenario based on real data, simulating the European Electricity Market environment, and comparing its performance when using several different market mechanisms.

Data Mining Approach to support the Generation of Realistic Scenarios for Multi-Agent simulation of Electricity Markets

This paper presents the Realistic Scenarios Generator (RealScen), a tool that processes data from real electricity markets to generate realistic scenarios that enable the modeling of electricity market players’ characteristics and strategic behavior. The proposed tool provides significant advantages to the decision making process in an electricity market environment, especially when coupled with a multi-agent electricity markets simulator. The generation of realistic scenarios is performed using mechanisms for intelligent data analysis, which are based on artificial intelligence and data mining algorithms. These techniques allow the study of realistic scenarios, adapted to the existing markets, and improve the representation of market entities as software agents, enabling a detailed modeling of their profiles and strategies. This work contributes significantly to the understanding of the interactions between the entities acting in electricity markets by increasing the capability and realism of market simulations.

Otimização do sítio web e google adwords

Relatório de estágio apresentado ao Instituto de Contabilidade e Administração do Porto para a obtenção do grau de Mestre em Empreendedorismo e Internacionalização, sob orientação de Doutora Ana Azevedo.

Improving discovery in the life sciences using semantic Web technologies and linked data: design principles for life sciences knowledge organization systems

Dissertation presented to obtain the Ph.D degree in Bioinformatics

A credibilidade da informação na web: estudo de práticas informacionais em contexto escolar

Apresentam-se os resultados parcelares de um estudo destinado a promover um melhor conhecimento das estratégias que os jovens em idade escolar (12-18 anos) consideram relevantes para avaliar as fontes de informação disponíveis na Internet. Para o efeito, foi aplicado um inquérito distribuído a uma amostra de 195 alunos de uma escola do 3o ciclo e outra do ensino secundário de um concelho do distrito do Porto. São apresentados e discutidos os resultados acerca da perceção destes alunos quanto aos critérios a aplicar na avaliação das fontes de informação disponíveis na Internet, na vertente da credibilidade. Serão apresenta- das as práticas que os jovens declaram ter relativamente ao uso de critérios de autoria, originalidade, estrutura, atualidade e de comparação para avaliar a credibilidade das fontes de informação. Em complemento, estes resultados serão comparados e discutidos com as perceções que os mesmos inquiridos demonstram possuir relativamente aos elementos que compõem cada um destes critérios. A análise dos dados obtidos é enquadrada e sustentada numa revisão da literatura acerca do conceito de credibilidade, aplicado às fontes de informação disponíveis na Internet. São ainda abordados alguns tópicos relaciona- dos com a inclusão de estratégias de avaliação da credibilidade da informação digital no modelo Big6, um dos modelos de desenvolvimento de competências de literacia da informação mais conhecidos e utilizados nas bibliotecas escolares portuguesas.

Declarative approach to data extraction of web pages

Thesis submitted to Faculdade de Ciências e Tecnologia of the Universidade Nova de Lisboa, in partial fulfilment of the requirements for the degree of Master in Computer Science

Exploring distributed computing tools through data mining tasks

Harnessing idle PCs CPU cycles, storage space and other resources of networked computers to collaborative are mainly fixated on for all major grid computing research projects. Most of the university computers labs are occupied with the high puissant desktop PC nowadays. It is plausible to notice that most of the time machines are lying idle or wasting their computing power without utilizing in felicitous ways. However, for intricate quandaries and for analyzing astronomically immense amounts of data, sizably voluminous computational resources are required. For such quandaries, one may run the analysis algorithms in very puissant and expensive computers, which reduces the number of users that can afford such data analysis tasks. Instead of utilizing single expensive machines, distributed computing systems, offers the possibility of utilizing a set of much less expensive machines to do the same task. BOINC and Condor projects have been prosperously utilized for solving authentic scientific research works around the world at a low cost. In this work the main goal is to explore both distributed computing to implement, Condor and BOINC, and utilize their potency to harness the ideal PCs resources for the academic researchers to utilize in their research work. In this thesis, Data mining tasks have been performed in implementation of several machine learning algorithms on the distributed computing environment.

História e património nos sítios web das câmaras municipais: a sugestão de boas prática e o evitar de maus procedimentos de divulgação

Trabalho de Projecto apresentado para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Práticas Culturais para Municípios

Web TV. Análise e melhores práticas em OCS nacionais e internacionais

Trabalho de projecto para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Novos Media e Práticas Web

NovaIntell - projecto de text-Mining para a língua portuguesa numa empresa de Gestão de Informação e Conhecimento

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação

Optimizações guiadas por dados reais em linguagens de domínio específico para a web

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do Grau de Mestre em Engenharia Informática

Combining open and closed world reasoning for the semantic web

Dissertação para obtenção do Grau de Doutor em Informática