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About

I am an associate professor at the Department of Computer Science of the Faculty of Science of the University of Porto and the coordinator of LIAAD , the Artificial Intelligence and Decision Support Lab of UP. LIAAD is a unit of INESC TEC (Laboratório Associado) since 2007. I am a PhD in Computer Science by U. Porto, MSc. on Foundations of Advanced Information Technology by the Imperial Collegeand BSc. in Applied Maths and Computer Science, currently Computer Science (U. Porto). My research interests are Data Mining and Machine Learning, in particular association rules, web  and text intelligence and data mining for decision support. My past research also includes Inductive Logic Programming and Collaborative Data Mining. I lecture courses related to programming, information processing, data mining, and other areas of computing. While at the Faculty of Economics, where I stayed from 1996 to 2009, I launched, with other colleagues, the MSc. on Data Analysis and Decisison Support Systems, which I coordinated from 2000 to April 2008. I lead research projects on data mining and web intelligence. I was the director of the Masters in Computer Science at DCC-FCUP from June 2010 to August 2013. I co-chaired international conferences (ECML/PKD 2015, Discovery Science 2009, ECML/PKDD 05 and EPIA 01), workshops and seminars in data mining and artificial intelligence. I was Vice-President of APPIA the Portuguese Association for Artificial Intelligence.

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Details

Details

  • Name

    Alípio Jorge
  • Cluster

    Computer Science
  • Role

    Centre Coordinator
  • Since

    01st January 2008
026
Publications

2022

LMMS reloaded: Transformer-based sense embeddings for disambiguation and beyond

Authors
Loureiro, D; Mário Jorge, A; Camacho Collados, J;

Publication
ARTIFICIAL INTELLIGENCE

Abstract

2022

The CirCor DigiScope Dataset: From Murmur Detection to Murmur Classification

Authors
Oliveira, J; Renna, F; Costa, PD; Nogueira, M; Oliveira, C; Ferreira, C; Jorge, A; Mattos, S; Hatem, T; Tavares, T; Elola, A; Rad, AB; Sameni, R; Clifford, GD; Coimbra, MT;

Publication
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS

Abstract

2022

The 5th International Workshop on Narrative Extraction from Texts: Text2Story 2022

Authors
Campos, R; Jorge, A; Jatowt, A; Bhatia, S; Litvak, M;

Publication
ADVANCES IN INFORMATION RETRIEVAL, PT II

Abstract

2022

Proceedings of Text2Story - Fifth Workshop on Narrative Extraction From Texts held in conjunction with the 44th European Conference on Information Retrieval (ECIR 2022), Stavanger, Norway, April 10, 2022

Authors
Campos, R; Jorge, AM; Jatowt, A; Bhatia, S; Litvak, M;

Publication
Text2Story@ECIR

Abstract

2022

Text2Icons: linking icons to narrative participants (position paper)

Authors
Valente, J; Jorge, A; Nunes, S;

Publication
Proceedings of Text2Story - Fifth Workshop on Narrative Extraction From Texts held in conjunction with the 44th European Conference on Information Retrieval (ECIR 2022), Stavanger, Norway, April 10, 2022.

Abstract
Narratives are used to convey information and are an important way of understanding the world through information sharing. With the increasing development in Natural Language Processing and Artificial Intelligence, it becomes relevant to explore new techniques to extract, process, and visualize narratives. Narrative visualization tools enable a news story reader to have a different perspective from the traditional format, allowing it to be presented in a schematic way, using representative symbols to summarize it. We propose a new narrative visualization approach using icons to represent important narrative elements. The proposed visualization is integrated in Brat2Viz, a narrative annotation visualization tool that implements a pipeline that transforms text annotations into formal representations leading to narrative visualizations. To build the icon visualization, we present a narrative element extraction process that uses automatic sentence extraction, automatic translation methods, and an algorithm that determines the actors' most adequate descriptions. Then, we introduce a method to create an icon dictionary, with the ability to automatically search for icons. Furthermore, we present a critical analysis and user-based evaluation of the results resorting to the responses collected in two separate surveys. © 2021 Copyright for this paper by its authors

Supervised
thesis

2021

Dataflower: harnessing heterogeneous hardware parallelism for creative applications

Author
Pedro Miguel Silva Carlos Sousa Ângelo

Institution
UP-FEUP

2021

Identification of Viable Dissolved Gas Analysis Subsets for Power Transformers

Author
José Pedro Ribeiro Ferreira Pinto

Institution
UP-FCUP

2021

Elasticidade em Lock-Free Hash-Tries

Author
João Miguel Chamiça Pereira

Institution
UP-FCUP

2021

Study of Electrical Protection function in grids with higher levels of Renewables that can cause a decrease of Short Circuit Currents and lead to grid Isolated systems

Author
João Pedro Alves Rodrigues da Costa

Institution
UP-FEUP

2021

Automotive Interior Sensing - Human Interaction Recognition

Author
Maria Carolina Silva Teixeira Pinto

Institution
UP-FEUP