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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
004
Publicações

2024

Indexing Portuguese NLP Resources with PT-Pump-Up

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

Publicação
CoRR

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).

2023

A survey on narrative extraction from textual data

Autores
Santana, B; Campos, R; Amorim, E; Jorge, A; Silvano, P; Nunes, S;

Publicação
ARTIFICIAL INTELLIGENCE REVIEW

Abstract
Narratives are present in many forms of human expression and can be understood as a fundamental way of communication between people. Computational understanding of the underlying story of a narrative, however, may be a rather complex task for both linguists and computational linguistics. Such task can be approached using natural language processing techniques to automatically extract narratives from texts. In this paper, we present an in depth survey of narrative extraction from text, providing a establishing a basis/framework for the study roadmap to the study of this area as a whole as a means to consolidate a view on this line of research. We aim to fulfill the current gap by identifying important research efforts at the crossroad between linguists and computer scientists. In particular, we highlight the importance and complexity of the annotation process, as a crucial step for the training stage. Next, we detail methods and approaches regarding the identification and extraction of narrative components, their linkage and understanding of likely inherent relationships, before detailing formal narrative representation structures as an intermediate step for visualization and data exploration purposes. We then move into the narrative evaluation task aspects, and conclude this survey by highlighting important open issues under the domain of narratives extraction from texts that are yet to be explored.

2023

From ISAD(G) to Linked Data Archival Descriptions

Autores
Koch, I; Pires, C; Lopes, CT; Ribeiro, C; Nunes, S;

Publicação
LINKING THEORY AND PRACTICE OF DIGITAL LIBRARIES, TPDL 2023

Abstract
Archives preserve materials that allow us to understand and interpret the past and think about the future. With the evolution of the information society, archives must take advantage of technological innovations and adapt to changes in the kind and volume of the information created. Semantic Web representations are appropriate for structuring archival data and linking them to external sources, allowing versatile access by multiple applications. ArchOnto is a new Linked Data Model based on CIDOC CRM to describe archival objects. ArchOnto combines specific aspects of archiving with the CIDOC CRM standard. In this work, we analyze the ArchOnto representation of a set of archival records from the Portuguese National Archives and compare it to their CIDOC CRM representation. As a result of ArchOnto's representation, we observe an increase in the number of classes used, from 20 in CIDOC CRM to 28 in ArchOnto, and in the number of properties, from 25 in CIDOC CRM to 28 in ArchOnto. This growth stems from the refinement of object types and their relationships, favouring the use of controlled vocabularies. ArchOnto provides higher readability for the information in archival records, keeping it in line with current standards.

Teses
supervisionadas

2022

E-APK: Energy Pattern Detection in Decompiled Android Applications

Autor
Nelson Alexandre Saraiva Gregório

Instituição
UP-FEUP

2022

Digital images as data and metadata: description requirements for information retrieval and semantic interoperability

Autor
Joana Patrícia de Sousa Rodrigues

Instituição
UP-FEUP

2022

Performative Sound Design - bio - control metaphors for sound design in performance art

Autor
Luís Alberto Teixeira Aly

Instituição
UP-FEUP

2022

Sistema de Formação Integrado para Enfermeiros e Auxiliares de Ação Médica em Bloco Operatório

Autor
Esmeralda Alves Monteiro Ferreira da Cruz

Instituição
UP-FEUP

2021

In situ real-time Zooplankton Detection and Classification

Autor
PEDRO NUNO DE QUEIRÓS SALCEDAS DE CARVALHO GERALDES

Instituição
IPP-ISEP