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Sobre

Sobre

Sérgio Nunes é Professor Associado do Departamento de Engenharia Informática da FEUP, Universidade do Porto e Investigador Sénior do INESC TEC. É Doutorado em Engenharia Informática (2010), na área da Recuperação de Informação, com trabalho focado no uso de caraterísticas temporais para estimar a relevância de informação. É Mestre em Gestão da Informação (2004) com trabalho desenvolvido na área da interoperabilidade entre sistemas de informação académicos.


Tem como principais interesses de investigação a área da recuperação de informação, a interação e visualização de informação, e os sistemas de informação em contexto web. No ensino, o foco são as áreas das bases de dados, das tecnologias da web, e da recuperação de informação, com a coordenação de diversas unidades curriculares em diferentes programas, nomeadamente o Programa Doutoral em Engenharia Informática, a Licenciatura e o Mestrado em Engenharia Informática, e o Mestrado em Multimédia.


Foi Diretor do U.Porto Media Innovation Labs (MIL), o Centro de Competências da Universidade do Porto com o objetivo de desenvolver a capacidade da universidade na área dos Media nas vertentes do ensino, investigação e inovação, promovendo colaborações entre as estruturas existentes e a articulação com parceiros externos.

Tópicos
de interesse
Detalhes

Detalhes

  • Nome

    Sérgio Nunes
  • Cargo

    Responsável de Área
  • Desde

    20 dezembro 2010
005
Publicações

2024

Indexing Portuguese NLP Resources with PT-Pump-Up

Autores
Almeida, R; Campos, R; Jorge, A; Nunes, S;

Publicação
CoRR

Abstract

2024

A Community-Driven Data-to-Text Platform for Football Match Summaries

Autores
Fernandes, P; Nunes, S; Santos, L;

Publicação
Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation, LREC/COLING 2024, 20-25 May, 2024, Torino, Italy.

Abstract

2024

Text2Story Lusa: A Dataset for Narrative Analysis in European Portuguese News Articles

Autores
Nunes, S; Jorge, AM; Amorim, E; Sousa, HO; Leal, A; Silvano, PM; Cantante, I; Campos, R;

Publicação
Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation, LREC/COLING 2024, 20-25 May, 2024, Torino, Italy.

Abstract

2023

Annotation and Visualisation of Reporting Events in Textual Narratives

Autores
Silvano, P; Amorim, E; Leal, A; Cantante, I; Silva, F; Jorge, A; Campos, R; Nunes, S;

Publicação
Proceedings of Text2Story - Sixth Workshop on Narrative Extraction From Texts held in conjunction with the 45th European Conference on Information Retrieval (ECIR 2023), Dublin, Ireland, April 2, 2023.

Abstract
News articles typically include reporting events to inform on what happened. These reporting events are not part of the story being told but are nonetheless a relevant part of the news and can pose a challenge to the computational processing of news narratives. They compose a reporting narrative, which is the present study's focus. This paper aims to demonstrate through selected use cases how a comprehensive annotation scheme with suitable tags and links can properly represent the reporting events and the way they relate to the events that make the story. In addition, we put forward a proposal for their visual representation that enables a systematic and detailed analysis of the importance of reporting events in the news structure. Finally, we describe some lexico-grammatical features of reporting events, which can contribute to their automatic detection. © 2023 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

2023

NewsLines: Narrative Visualization of News Stories

Autores
Costa, M; Nunes, S;

Publicação
Proceedings of Text2Story - Sixth Workshop on Narrative Extraction From Texts held in conjunction with the 45th European Conference on Information Retrieval (ECIR 2023), Dublin, Ireland, April 2, 2023.

Abstract
Visual representations have the potential to improve information understanding. We explore this idea in the development of NewsLine, an open-source web-based prototype that focuses on narrative visualizations of news content. Having structured data as input, the prototype produces a storyline which showcases the narrative's events and participants, allowing the user to interact with the visualization in a number of ways. We built an information hub around the storyline to allow for multiple levels of exploration, specifically the main visualization, the event information module, and the sidebar. The visualization depicts the sequence of events that make up a news story, as well as the interactions between the involved parties in each event. The event information module presents additional information on a particular event. The sidebar is the “control center” of the visualization, unlocking a number of interactions and configurations. The prototype was evaluated with a user study with journalists and also with an online survey which gathered feedback from 178 potential end users. From these, 106 participants (60.6%) provided a rating of four or above (one to five scale) when asked to quantify their interest in using the application. Moreover, participants were asked to rank the importance of the visualization elements used. The results highlight that two elements stand out as the most important, the events and the entities. Overall, the participants generally found the application to be useful, but in need of some work in order for it to be made available to a broader public. © 2023 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

Teses
supervisionadas

2023

Federation Solutions for Linked Data Applications

Autor
Tiago Gonçalves Gomes

Instituição
UP-FEUP

2023

Information Retrieval over Linked Data Archives

Autor
Cláudia Inês da Costa Martins

Instituição
UP-FEUP

2023

Connect-the-Dots: Artificial Intelligence and Automation in Investigative Journalism

Autor
Joana Rodrigues da Silva

Instituição
UP-FEUP

2023

Evaluation of Text Diversity over time for Automatically Generated Texts in Sports Journalism

Autor
José David Souto Rocha

Instituição
UP-FEUP

2023

Text Information Retrieval in Tetun

Autor
Gabriel de Jesus

Instituição
UP-FEUP