2005
Authors
Gama, J; Camacho, R; Brazdil, P; Jorge, A; Torgo, L;
Publication
ECML
Abstract
2005
Authors
Jorge, A; Torgo, L; Brazdil, P; Camacho, R; Gama, J;
Publication
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Abstract
2005
Authors
Gama, J; Camacho, R; Brazdil, P; Jorge, A; Torgo, L;
Publication
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Abstract
2012
Authors
Morgado, IC; Paiva, ACR; Faria, JP; Camacho, R;
Publication
2012 1st International Workshop on Realizing AI Synergies in Software Engineering, RAISE 2012 - Proceedings
Abstract
This paper proposes a new approach to reduce the effort of building formal models representative of the structure and behaviour of Graphical User Interfaces (GUI). The main goal is to automatically extract the GUI model with a dynamic reverse engineering process, consisting in an exploration phase, that extracts information by interacting with the GUI, and in a model generation phase that, making use of machine learning techniques, uses the extracted information of the first step to generate a state-machine model of the GUI, including guard conditions to remove ambiguity in transitions. © 2012 IEEE.
2011
Authors
Rocha, A; Henriques, MR; Lopes, JC; Camacho, R; Klein, M; Modena, G; Van de Ven, P; McGovern, E; Tousset, E; Gauthier, T; Warmerdam, L;
Publication
2012 25TH INTERNATIONAL SYMPOSIUM ON COMPUTER-BASED MEDICAL SYSTEMS (CBMS)
Abstract
FP7 ICT4Depression project aims at providing a set of tools to,further improve both patient outcome and increase of access to treatment of the patients suffering from major depression. This article describes the Information Systems (IS) architecture used in the project. ICT4Depression uses a service oriented architecture as means of bringing together different kinds of information concerning the patient, the therapeutic modules he is advised to follow and the sensors used to assess his status.
2010
Authors
Correia, F; Camacho, R; Lopes, JC;
Publication
KDIR 2010: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON KNOWLEDGE DISCOVERY AND INFORMATION RETRIEVAL
Abstract
Collaborative Data Mining (CDM) develops techniques to solve complex problems of data analysis requiring sets of experts in different domains that may be geographically separate. An important issue in CDM is the sharing of experience among the different experts. In this paper we report on a framework that enables users with different expertise to perform data analysis activities and profit, in a collaborative fashion, from expertise and results of other researchers. The collaborative process is supported by web services that seek for relevant knowledge available among the collaborative web sites. We have successfully designed and deployed a prototype for collaborative Data Mining in domains of Molecular Biology and Chemoinformatics.
The access to the final selection minute is only available to applicants.
Please check the confirmation e-mail of your application to obtain the access code.