Research Group on
Knowledge & Learning Technologies
(K&LT)
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Introduction to
Knowledge & Learning Technologies (K&LT) group
Knowledge-based Systems (KBS) correspond to an area where there is
an explicit separation between Knowledge and Inference. Expert
Systems, Data Mining, Intelligent Tutors are examples of KBS.
Knowledge play an important role in KBS. Nowadays, Ontologies are
receiving attention, namely due to the importance of concepts and
their relation for the Intelligent Agents, Semantic Web, and
Knowlewdge Management.
Machine Learning techniques envisage obtaining automatically, or
semi-automatically, knowledge from data. Neural Networks, Decision
Trees, Case-based Reasoning are just some of the used techniques. Data
Mining joins AI based Machine Learning with Statistics based techniques
(e.g. K-means) to allow a powerful set of tools to be used in the
Knowledge Discovery effort in Information Systems.
The main objective of the Knowledge & Learning Technologies group is
to concentrate critical mass around these technologies in order to allow
a Knowledge Society and Economy built in a correct way. We claim
that “Knowledge” must not be seen just as one more keyword, and that
without agents with Knowledge and Machine Learning technologies the
Knowledge Society and Economy will be too limited.
The main areas where this group works are:
- Expert Systems
- Intelligent Tutoring Systems
- Ontologies
- Machine Learning, Data Mining, including Neural Networks
- Intelligent Agents
- Semantic Web
- Knowledge Management
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Knowledge & Learning Technologies group has obtained a meaningful
scientific recognition during the last years.
This recognition is clear from the quality of the main publications, in
scientific journals with high impact factors (e.g. the maximum is 2.202,
and other 5 publications are close to 1).
During the last years this group had 6 projects (SANSKI, DAMICE,
ONTOMAPPER, EDGAR, Agents&Markets, EMUSSL, and TINSEL) and 3
new project will start in 2007 (IFRA, COPSRO, and COALESCE).
The group covers a great variety of areas. The area of Data Mining is
obtaining results at different levels, namely in terms of publications, but
also in projects (DAMICE, EMUSSL and more recently COPSRO and
IFRA). The area of Ontologies has obtained results in the projects
(SANSKI, ONTOMAPPER, and EDGAR, and more recently in IFRA and
also in COPSRO) and in good international connections. The area of
Intelligent Tutoring Systems has the TINSEL project and also cooperates
with the Intelligent Energy Systems group in another project (APRICOT).
The area of Intelligent Agents has also importance due to the
Agents&Markets project and also due to the publications. Notice that
Agent-based systems are a technology covered by all groups of GECAD.
Cooperation with international groups is established in several works,
namely in Ontologies. Two researchers of this group, Nuno Silva and
Jorge Santos, were during some months in Germany in FZI
(Forschungzentrum Informatik) and AIFB (Angewandte Informatik
und Formale Beschreibungsverfahren) where they contacted with some
of the most prominent researchers of Ontologies (Steffen Staab,
Alexander Maedche, Rudi Studer, and Rudi Studer). As a result of the
stay there, two world reference platforms (MAFRA and FONTE) were
developed by our researchers. These platforms are now used in 4
European R&D projects, namely, in Harmonise (IST-2000-29329),
Harmo-Ten (eTEN C510828), Satine (IST-1-002104-STP), and Artemis
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(IST-1-002103-STP). Publications with international authors have also
been done in Ontologies, Intelligent Agents and Data Mining areas.
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Researchers of
Knowledge & Learning Technologies (K&LT) group
Group Coordinator: Fátima Rodrigues
email: [email protected]
PhD Researchers
Armando Silva Vieira
Fernando Augusto Cruz e Silva Mouta
João Manuel Simões da Rocha
José António dos Reis Tavares
Luiz Felipe Rocha de Faria
Maria de Fátima Coutinho Rodrigues
Maria João Monteiro Ferreira Viamonte
Nuno Alexandre Pinto da Silva
Carlos Fernando da Silva Ramos (AI&DS group)
Nuno Filipe Teixeira Malheiro (IES group)
Paulo Alexandre Gandra de Sousa (CI group)
Non-PhD Researchers
António Constantino Lopes Martins
António Jorge dos Santos Pereira
Fernando Jorge Ferreira Duarte
Gustavo Soares Santos
Hélio Artur Mendes Martins
João Manuel Maia Duarte
Ludimila Luiza de Lima Gabriel
Luís André Andrade da Silva Oliveira
Nuno Bettencourt
Paulo Alexandre Fagueiro Oliveira Maio
Paulo Jorge Machado Oliveira
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Specific Projects of the
Knowledge & Learning Technologies (K&LT) group
SANSKI - POCTI/41830- Semi-automatic Negotiation Services for Knowledge
Interoperability [2002-2005] – FCTI
DAMICE – POCTI/39744 - Power Systems Consumer Profiles and Contracting
Strategies supported by Data Mining [2002-2005] – FCT
ONTOMAPPER - POSI/41818- Ontology Automatic Mapping [2002-2005] – FCT
EDGAR - POSC/61307 - Exploiting Ontology Engineering Process Information for
Semi-Automatic Knowledge Interoperability [2005-2008] – FCT
Agents&Markets - POSI/56260 - Agent based Market Simulation [2005-2008] FCT
TINSEL - POSI/61843 – Intelligent Tutors for Electrical Installation Design [20052008] – FCT
EMUSSL - POSC/61924 - Ensemble Methods for Unsupervised and Semi-Supervised
Learning [2005-2008] – FCT
IFRA - PTDC/70168 - Improving Financial Risk Analysis with advanced Data-Mining
tools [2007-2010] – FCT
COPSRO - PTDC/EIA/69988/2006 - Computational Approach to Ontology Profiling
of Scientific Research Organisations [2007-2010] – FCT
COALESCE - PTDC/EIA/74417/2006 - Collaboration-based Information and
Recommendation Retrieval Systems [2007-2010] – FCT
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Budgets of Projects of
Knowledge & Learning Technologies (K&LT) group
SANSKI - € 45.000,00
DAMICE - € 32.000,00
ONTOMAPPER - € 10.000,00
EDGAR - € 75.000,00
Agents&Markets - € 74.000,00
TINSEL - € 62.500,00
EMUSSL - € 31.896,00
IFRA - € 62.000,00
COPSRO - € 146.837,00
COALESCE - € 117.984,00
iDESK (FCT Reequipment) - € 70.000,00
IPP Reequipment - € 46500,00
iDESK-RUN (FCT Basic Fund) - € 89.487,50
ISEP Basic Fund - € 5.000,00
Post-PhD hiring fund – € 220.000,00
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SANSKI - POCTI/41830- Semi-automatic Negotiation
Services for Knowledge Interoperability
Project Leader: João Rocha
email: jsr@ isep.ipp.pt
SANSKI
(Semi-automatic
Negotiation
Service
for
Knowledge
Interoperability) is a project supported by FCT that started in
January/2002 with the duration of 3 years. This project proposed
approaches, methodologies and solutions, respecting the negotiation
and translation of communication parameters, namely concerning
knowledge sharing models, in order to achieve interoperability between
heterogeneous entities. Several prototypes were developed in order to
validate the suggested approaches.
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DAMICE – POCTI/39744 - Power Systems Consumer
Profiles and Contracting Strategies supported by Data
Mining
Project Leader: Fátima Rodrigues
email: [email protected]
DAMICE (Power Systems Consumer Profiles and Contracting Strategies
supported by Data Mining) envisaged the application of Data Mining
and Knowledge Discovery techniques to the existing information about
electric energy consumers to obtain the characterization of different
consumer profiles. The obtained knowledge is important for the
suggestion of the most adequate contracts to be established.
EDP cooperated with GECAD in this project.
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0.6
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Cluster 1
Cluster 2
Cluster 3
Cluster 4
Cluster 6
Cluster 7
Cluster 8
Cluster 9
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Cluster 5
ONTOMAPPER - POSI/41818- Ontology Automatic
Mapping
Project Leader: João Rocha
email: jsr@ isep.ipp.pt
ONTOMAPPER (Ontology Automatic Mapping) is a project supported
by FCT that started in March/2002 with the duration of 3 years. The
correct and coherent knowledge definition, its representation,
communication, share and respective methods, give rise to several
problems. Also, when adopting and sharing ontologies, the elements to
reason about knowledge exist, but other complementary processes are
needed in order to entities agreed on the models and its meanings. In
this project it was suggested to employ standard technology, like the
FIPA and KQML agent communication languages (ACL), emergent
standards for representing and structure information like XML/S, RDF/S
and DAML+OIL. Concerning ontologies, recent tools like OILEd and
OntoEdit ontology editors, Protégé as a methodology and Ontobroker
and FaCT based reasoning engines were used.
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EDGAR - POSC/61307 - Exploiting Ontology
Engineering Process Information for Semi-Automatic
Knowledge Interoperability
Project Leader: João Rocha
email: jsr@ isep.ipp.pt
MAFRA Toolkit is a service-oriented tool for mapping ontologies
developed by the research team of this Project. Semantic bridges have
a limited support in this tool.
Although all the advantages of this approach, several semantic
relations are suggested for the same entities’ group. These are clearly
ambiguity situations, since many services are activated due to a
reduced number of imposed constraints.
EDGAR project envisages providing the decreasing of the number of
ambiguous resulting from the similarity measures. Research in the áreas
of Ontology merging and pattern-based Ontology Engineering are
being used. A formal approach, using another platform developed by
this group, FONTE, is used.
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Agents&Markets - POSI/56260 - Agent based Market
Simulation
Project Leader: Carlos Ramos
email: [email protected]
Agents&Markets (Agent-based Market Simulation) envisages the use of
Multi-Agent Systems technologies in Markets Simulation. This will be an
innovative proposal combining the following aspects: Agent-based
Simulation; Consumer Behaviour Model; Electronic Market Analysis;
Negotiation Mechanisms; Strategic Behaviours; Machine Learning and
Data Mining; and other participants’ behaviour analysis with Game
Theory. The basic idea of this project is to simulate markets using
Intelligent Agents technology in order to be exhibited a timedependant strategic behaviour, making decisions considering the other
participants behaviour (Consumer Behaviour Model, Game-Theoretic
based Scenario Analysis) and providing the automation of the learning
using the past interactions. The developed system will not be just a
Market Simulator. It is envisaged a tool to support decision-making for
one or more market participants. Two different test cases are
considered: Electricity Markets and Electronic Commerce.
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TINSEL - POSI/61843 – Intelligent Tutors for Electrical
Installation Design
Project Leader: Luiz Faria
email: [email protected]
Electrical Installations design combines academic and empirical
knowledge.
TINSEL project envisages the development of an Intelligent Tutoring
System to support Electrical Installations designers, technical staff and
Electrical Engineering students.
The Project involves the development of the user model in order to
support the pedagogical options of the tutoring system. A library with
real cases will be used in the mapping of the main features of the cases
with the domain concepts. Case-based reasoning will be used to select,
adapt and store real cases, allowing to customize courses and to
improve the adaptive capabilities to the trainee. Grouping and
Comparison techniques will be used in the definition of the students’
stereotypes.
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EMUSSL - POSC/61924 - Ensemble Methods for
Unsupervised and Semi-Supervised Learning
Project Coordinator at GECAD: Fátima Rodrigues
email: [email protected]
Data clustering or unsupervised learning is an important but difficult
problem. The objective of clustering is to partition a set of unlabelled
objects into homogeneous groups or clusters. Quantitative evaluation of
the quality of clustering results is difficult due to the inherent
subjectivity of the notion of cluster. Semi-supervised learning algorithms
make use of both labelled and unlabelled samples and have been the
focus of much recent research by the machine learning and pattern
recognition communities. Semi-supervised learning has been typically
viewed from a supervised learning point of view, as a being a
classification problem with some missing labels. This perspective suggests
the use of supervised ensemble methods to semi-supervised problems.
This research direction will be exploited in the project. Additionally, one
of the main threads of this project will be to address semi-supervised
learning as an unsupervised learning problem with some additional
knowledge/constraints. This perspective will allow semi-supervised and
unsupervised problems to be addressed in an integrated fashion, which
we will do with a strong emphasis on ensemble methods.
This project involves IT (Telecommunications Institute) and GECAD.
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IFRA - PTDC/70168 - Improving Financial Risk
Analysis with advanced Data-Mining tools
Project Coordinator at GECAD: Armando Vieira
email: asv@ isep.ipp.pt
Predicting when a company may declare bankruptcy is a problem of
great importance for creditors - banks, bondholders and suppliers - and
also for other stakeholders such as shareholders, employees, customers
and State.
In an increasingly globalized economy, bankruptcy results both in huge
economic losses and tremendous social impact. More important than
predicting the insolvency is to determine the probability to become so.
This is a complex problem, normally analysed by conventional statistical
techniques such as Linear Discriminant.
However recent techniques, as Genetic Algorithms, Neuronal Networks,
and Support Vector Machines had shown to be more robust and
efficient to analyze this type of problem as well as related others. The
objective of this project is to use these techniques of data classification in
the field of financial risk and decision support, namely bankruptcy
prediction.
This project involves IST, University of Coimbra, University of Minho, and
GECAD. The Bank of Portugal will cooperate in this project.
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COPSRO - PTDC/EIA/69988/2006 - Computational
Approach to Ontology Profiling of Scientific Research
Organisations
Project Coordinator at GECAD: Fátima Rodrigues
email: [email protected]
The main objective of this research work is to develop a methodology
for ontology profiling scientific research organisations, including:
-A reliable and valid research subject extraction method developing
text mining techniques.
-An effective method for establishing within-organisation similarities
between the ontology items.
-Adequate clustering methods for representing a research organisation
by a set of possibly overlapping or fuzzy subject clusters.
-Optimally mapping the subject clusters to the subject area ontology to
reveal organisation’s profile.
-Interpretation and evaluation of individual organisation profiles.
-Combination of individual profiles into an aggregate profile.
-Characterization of aggregate profiles by rule extraction.
-Experimental verification of the method.
The proposed methodology will be applied to scientific research
organisations of computer science, specifically, Computer Science
Departments of Universities in Portugal and UK, having as ontology of
reference the ACM Classification System. This project involves CENTRIA
and GECAD.
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COALESCE - PTDC/EIA/74417/2006 - Collaborationbased Information and Recommendation Retrieval
Systems
Project Leader: Nuno Silva
email: [email protected]
In order to take advantage of the huge amount of data on the Web,
one has to collect, filter and assemble it, relating facts and documents,
as well as considering the use that each one (or community) makes of
them.
The project aims to research on methods and tools able to simplify and
automate the management of information, through retrieval,
integration and recommendation of information from multiple public
and private repositories in a semantic (described through ontologies or
folksonomies) and recommended fashion (according to semantic social
networks emerging in the context of the Social Web.
The envisaged system will be wrapped-up with a tool in the form of a
Semantic Desktop, as the interface between the user and public
repositories, either on the Web, PCs or mobile devices. As the Semantic
Desktop and complementing technologies improves their features, the
local vs. Web dichotomy tends to disappear, promoting the
transparency between the physical location and type of information.
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Main Publications in Journals of the
Knowledge & Learning Technologies (K&LT) group
•
V. Matias, G. Öhl, J.C. Soares, N. P. Barradas, A. Vieira, P.P. Freitas, S.
Cardoso; Determination of the composition of light thin films with artificial
neural networks analysis of Rutherford backscattering experiments; Physical
Review E 67, article 046705; 2003; IF=2.202.
•
H. Pinho, A. Vieira, N. Nené, N. Barradas; Artificial neural network analysis
of multiple IBA spectra; Nuclear Instruments and Methods B; 2005; IF=1.181.
•
N. P. Barradas, R. N. Patrício, H. F. R. Pinho, A. Vieira; A general artificial
neural network for analysis of RBS data of any element with Z between 18
and 83 implanted into any lighter one- or two-element target; Nuclear
Instruments and Methods B; 219; pp. 105-109; 2003; IF=1.041.
•
V. Figueiredo, F. Rodrigues, Z. Vale, J. B. Gouveia; An Electric Energy
Consumer Characterization Framework Based on Data Mining Techniques;
IEEE Transaction on Power Systems; 20(2); pp 596-602; 2005; IF=0.951
•
N. Nene, N. P. Barradas, A. Vieira; Artificial neural network analysis of RBS
and ERDA spectra of multilayered multielemental samples; Nuclear
Instruments and Methods B; 246(2); pp. 471-478; 2006; IF=0.946
•
M. J. Viamonte, C. Ramos, F. Rodrigues, J. Cardoso; ISEM: A Multi-Agent
Simulator For Testing Agent Market Strategies; IEEE -Transactions on
Systems, Man and Cybernetics, Part C – Special Issue on Game-Theoric
Analysis and Stochastic Simulation of Negotiation Agents; 36(1); pp. 107-113;
2006; IF=0.885.
•
P. Sousa; C. Ramos, J. Neves; The Fabricare Scheduling Prototype Suite:
Agent interaction and knowledge base; Journal of Intelligent Manufacturing;
14(5); pp. 441-455; Kluwer Academic Publishers; 2004; IF=0.595.
•
A. Vieira, N. Barradas; A training algorithm for classification of high
dimensional data; Neurocomputing; 50C; pp. 461-472; 2003; IF=0.592.
•
P. Sousa, C. Ramos, J. Neves;The Fabricare System; Production Planning &
Control; 15(2); pp. 156-165; Taylor & Francis; 2004; IF=0.326.
•
Y. Chevaleyre, P. E. Dunne, U. Endriss, J. Lang, M. Lemaître, N. Maudet, J.
Padget, S. Phelps, J.A. Rodriguez-Aguilar, P. Sousa; Issues in Multiagent
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Resource Allocation; Informatica; 30(1); pp. 3-31; Slovenian Society
Informatika; 2006; IF=0.221
•
L. Faria, Z. Vale, C. Ramos, A. Marques; Diagnosis tasks intelligent training
based on a model tracing approach; International Journal of Engineering
Intelligent Systems; Special Issue on Knowledge Engineering; CRL Publishing;
13(4), pp. 223-230; 2005 IF=0.093
•
N. Malheiro, Z. Vale, C. Ramos, M. Cordeiro, A. Gomes, A. Marques, Vieira
Couto; Decision Support For Power System Control Centers – A Model Based
Reasoning Component; International Journal of Engineering Intelligent
Systems, Special Issue on Knowledge Engineering; CRL Publishing; 13(4); pp.
205-212; 2005; IF=0.093
•
N. Silva, J. Rocha; Service oriented semi-automatic ontology mapping;
International Journal of Engineering Intelligent Systems; Special Issue on
Knowledge Engineering; CRL Publishing; 13(4); pp. 253-258; 2005; IF=0.093.
•
N. Silva, J. Rocha; Multi-dimension Service-Oriented Ontology Mapping;
International Journal of Web Engineering and Technology (IJWET); 2004
•
N. Silva, J. Rocha; Multidimensional service-oriented ontology mapping;
International Journal of Web Engineering and Technology; Inderscience
Publishers; 2(1); pp. 50-80; 2005
•
J. Duarte, A. Fred, F. Rodrigues, J. Duarte, S. Ramos, Z. Vale; Weighted
Evidence Accumulation Clustering using Subsampling to support the
definition of Electrical Tariffs; WSEAS Transactions on Power Systems; 12(1);
pp. 2001-2009; 2006
•
M. J. Viamonte, C. Ramos, F. Rodrigues, J. Cardoso; ISEM: A Multi-Agent
System That Simulates Competitive Electronic MarKetPlaces; Selected for
publication in an upcoming special issue of the International Journal of
Engineering Intelligent Systems in 2007
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Some other Publications of the
Knowledge & Learning Technologies (K&LT) group
•
J. Santos, S. Staab; Engineering a Complex Ontology with Time; Workshop of
Ontologies and Distributed Systems; 18th International Joint Conference on
Artificial Intelligence (IJCAI) ; Acapulco, México; 2003
•
P. Oliveira, F. Rodrigues, P. Henriques; An Ontology-Based Approach For
Data Cleaning; 11th International Conference on Information Quality, MIT,
pp. 307-320, Boston, USA; 2006
•
O. Gilson, N. Silva, P. Grant, M. Chen, J. Rocha; Online Information
Visualization: Automatic Mapping of Data Entities to Representation
Artefacts; Fifth International Semantic Web Conference; Athens (GA), USA;
2006
•
M. J. Viamonte, C. Ramos, F. Rodrigues, J. Cardoso; A Market Simulator for
Analysing Agent Market Strategies; Building the Knowledge Economy: Issues,
Applications, Case Studies; IOS Press; pp. 284-291; 2003
•
M. J. Viamonte, C. Ramos, J. Cardoso, F. Rodrigues; Learning User Preference
Models and Business Strategies for E-Commerce; Building the Knowledge
Economy; IOS Press; 2004
•
M. J. Viamonte, C. Ramos, F. Rodrigues, J. Cardoso; ISEM: A Multi-Agent
System for Testing the Behaviour of Electronic Market Participants;
Innovation and the Knowledge Economy - Issues, Applications and Case
Studies; Paul Cunningham, Miriam Cunningham (editors); IOS Press. ISBN
1574-1230; pp. 857-864; 2005
•
N. Malheiro, Z. Vale, C. Ramos, V. Couto; Decision Support with Incomplete
Information In Critical Situations – An Application For Power System Control
Centers; Knowledge and Decision Technologies; Z. Vale, C. Ramos and L.
Faria (eds.); ISBN 972-8688-39-3; 2006
•
J. Duarte, A. Fred, F. Rodrigues, J. Duarte; Clustering Evidence Accumulation
Clustering using the Weight of the Cluster Ensemble; Knowledge and
Decision Technologies; Z. Vale, C. Ramos and L. Faria (eds.); pp. 83-90; ISBN
972-8688-39-3; 2006
•
F. Rodrigues, C. Ramos, P. Henriques; A unifying Data Preparation
Framework For Knowledge Discovery in Databases; Knowledge and
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Decision Technologies; Z. Vale, C. Ramos and L. Faria (eds.); pp. 59-65; ISBN
972-8688-39-3; 2006
•
P. Oliveira, F. Rodrigues, P. Henriques; Data Cleaning By Reusing Domain
Knowledge; Knowledge and Decision Technologies; Z. Vale, C. Ramos and L.
Faria (eds.); pp. 67-74; ISBN 972-8688-39-3; 2006
•
M. J. Viamonte, C. Ramos, F. Rodrigues, J. C. Cardoso; A Multi-Agent System
To Support Decision Making In Competitive Electronic Marketplaces;
Knowledge and Decision Technologies; Z. Vale, C. Ramos and L. Faria (eds.);
pp. 189-195; ISBN 972-8688-39-3; 2006
•
N. Bettencourt, P. Maio, A. Pongó, N. Silva, J. Rocha; Systematization and
Clarification of Semantic Web Annotation Terminology; Knowledge and
Decision Technologies; Z. Vale, C. Ramos and L. Faria (eds.), pp. 67-74; ISBN
972-8688-39-3; 2006
•
P. Maio, N. Bettencourt, N. Silva, J. Rocha; Ontology Mapping Negotiation
Based on Categorization of Semantic Bridges; Knowledge and Decision
Technologies; Z. Vale, C. Ramos and L. Faria (eds.);ISBN 972-8688-39-3;
2006
•
L. Faria, A. Gomes, A. Silva, Z. Vale, C. Ramos, G Santos, F. Ferreira;
Intelligent Tutor for Electrical Installation Design; Knowledge and Decision
Technologies; Z. Vale, C. Ramos and L. Faria (eds.); ISBN 972-8688-39-3;
2006
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PhD and MSc Thesis of
Knowledge & Learning Technologies (K&LT) group
PhD Thesis
•
Nuno Silva; Multi-Dimensional Service-Oriented Ontology Mapping; PhD
Thesis in Informatics; Universidade de Trás-os-Montes e Alto Douro (UTAD);
2004
•
Maria João Viamonte; Mercados Electrónicos Baseados em Agentes – uma
abordagem orientada ao conhecimento considerando estratégias dinâmicas
(Agent-based Electronic Markets – a knowledge oriented approach
considering dynamic strategies); PhD Thesis in Informatics; UTAD; 2004
•
Nuno Malheiro; Processamento Inteligente de Informação em Situações
Críticas – Uma Abordagem Considerando Informação Incompleta
(Intelligent Information Processing in Critical Situations – an approach
considering Incomplete Information); PhD Thesis in Informatics; UTAD; 2005
•
Ramiro Gonçalves; Modelo Explicativo das Iniciativas de Comércio
Electrónico (Initiative Explaining Model in Electronic Commerce), PhD Thesis
in Informatics; UTAD; 2005
•
Jorge Santos; Integração de Conhecimento Temporal em Sistemas
Inteligentes (Temporal Knowledge Integration in Intelligent Systems); PhD
Thesis in Informatics; UTAD; 2007
•
Jorge Duarte; Clustering algorithms, validation indices and ensemble
methods; PhD Thesis in Informatics; UTAD; 2007
•
Paulo Oliveira; Data problems detection operations and cleaning based on
dependency graphs; PhD Thesis in Informatics; University of Minho; 2007
MSc Thesis
•
Vera Figueiredo; Caracterização de Perfis de Consumidores de Energia
Eléctrica Usando Técnicas de Data Mining (Electrical Energy Consumir
Profile Characterization Using Data Mining Techniques), MSc Thesis, FEUP,
2003
•
António Soares, Sistemas Automáticos de Percurso e Recolha de Informação
na WEB (Automatic Systems for Information Retrieval in the WEB), MSc
Thesis in Informatics, UTAD, 2004
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•
Jorge Borges, Modelo de Data Warehouse para Análise de Serviços de
Internet (Data Warehouse Model for Internet Service Analysis), MSc Thesis in
Informatics, UTAD, 2004
•
S. Ramos; Utilização de Técnicas de Data Mining para apoio aos Agentes dos
Mercados Retalhistas de Energia Eléctrica (Data Mining Techniques for
supporting Agents in Electricity Retail Markets); MSc Thesis, Instituto Superior
Técnico; 2006
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