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About

About

Sérgio Nunes is an Associate Professor at the Department of Informatics Engineering at FEUP, University of Porto, and a Senior Researcher at INESC TEC. He holds a PhD in Information Retrieval (2010) focused on using temporal features for relevance estimation, and a MSc in Information Management (2004).


His main research interests are in information retrieval and web information systems. He teaches databases, web technologies and information retrieval in different programs, namely the Informatics Engineering Doctoral Program, the Informatics Engineering Bachelor and Masters, and the Multimedia Masters.


Was the Director of the U.Porto Media Innovation Labs (MIL), an Excellence Center of the University of Porto, with the mission of developing the university's capacity in the field of Media in teaching, research and innovation activities by promoting collaborations between existing university structures and articulation with external partners.

Interest
Topics
Details

Details

  • Name

    Sérgio Nunes
  • Role

    Area Manager
  • Since

    20th December 2010
  • Nationality

    Portugal
  • Contacts

    +351222094199
    sergio.nunes@inesctec.pt
005
Publications

2024

Indexing Portuguese NLP Resources with PT-Pump-Up

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

Publication
CoRR

Abstract

2024

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

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

Publication
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

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

Publication
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

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

Publication
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

Authors
Costa, M; Nunes, S;

Publication
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).

Supervised
thesis

2023

Building a search engine on a sports-related platform

Author
Ricardo Filipe da Silva Néri Marques Carvalho

Institution
UP-FEUP

2023

Access Control in Linked Data Archives

Author
Tiago Gonçalves da Silva

Institution
UP-FEUP

2023

Federation Solutions for Linked Data Applications

Author
Tiago Gonçalves Gomes

Institution
UP-FEUP

2023

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

Author
Joana Rodrigues da Silva

Institution
UP-FEUP

2023

Visualizing News Stories from Annotated Text

Author
Catarina Justo dos Santos Fernandes

Institution
UP-FEUP