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Sobre

Sobre

Sérgio Nunes é Professor Auxiliar 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.

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.

Tem como principais interesses de investigação a Recuperação de Informações e os Sistemas de Informação na 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, o Mestrado em Engenharia Informática e o Mestrado em Multimédia.

Tópicos
de interesse
Detalhes

Detalhes

  • Nome

    Sérgio Nunes
  • Cluster

    Informática
  • Cargo

    Responsável de Área
  • Desde

    20 dezembro 2010
004
Publicações

2022

Text2Icons: linking icons to narrative participants (position paper)

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

Publicação
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

2021

Managing research the wiki way

Autores
Devezas, JL; Nunes, S;

Publicação
XRDS

Abstract

2021

Brat2Viz: a Tool and Pipeline for Visualizing Narratives from Annotated Texts

Autores
Amorim, E; Ribeiro, A; Santana, BS; Cantante, I; Jorge, A; Nunes, S; Silvano, P; Leal, A; Campos, R;

Publicação
Proceedings of Text2Story - Fourth Workshop on Narrative Extraction From Texts held in conjunction with the 43rd European Conference on Information Retrieval (ECIR 2021), Lucca, Italy, April 1, 2021 (online event due to Covid-19 outbreak).

Abstract
Narrative Extraction from text is a complex task that starts by identifying a set of narrative elements (actors, events, times), and the semantic links between them (temporal, referential, semantic roles). The outcome is a structure or set of structures which can then be represented graphically, thus opening room for further and alternative exploration of the plot. Such visualization can also be useful during the on-going annotation process. Manual annotation of narratives can be a complex effort and the possibility offered by the Brat annotation tool of annotating directly on the text does not seem sufficiently helpful. In this paper, we propose Brat2Viz, a tool and a pipeline that displays visualization of narrative information annotated in Brat. Brat2Viz reads the annotation file of Brat, produces an intermediate representation in the declarative language DRS (Discourse Representation Structure), and from this obtains the visualization. Currently, we make available two visualization schemes: MSC (Message Sequence Chart) and Knowledge Graphs. The modularity of the pipeline enables the future extension to new annotation sources, different annotation schemes, and alternative visualizations or representations. We illustrate the pipeline using examples from an European Portuguese news corpus. Copyright © by the paper's authors.

2021

A Review of Graph-Based Models for Entity-Oriented Search

Autores
Devezas, J; Nunes, S;

Publicação
SN Computer Science

Abstract

2021

A Survey on User Interaction with Linked Data

Autores
Aguiar, M; Nunes, S; Giesteirad, B;

Publicação
Proceedings of the Sixth International Workshop on the Visualization and Interaction for Ontologies and Linked Data co-located with the 20th International Semantic Web Conference (ISWC 2021), Virtual Conference, 2021.

Abstract
Since the beginning of the Semantic Web and the coining of the term Linked Data in 2006, more than one thousand datasets with over sixteen thousand links have been published to the Linked Open Data Cloud. This rising interest is fuelled by the benefits that semantically annotated and machine-readable information can have in many systems. Alongside this growth we also observe a rise in humans creating and consuming Linked Data, and the opportunity to study and develop guidelines for tackling the new user interaction problems that arise with it. To gather information on the current solutions for modelling user interaction for these applications, we conducted a study surveying the interaction techniques provided in the state of the art of Linked Data tools and applications developed for users with no experience with Semantic Web technologies. The 18 tools reviewed are described and compared according to the interaction features provided, techniques used for visualising one instance and a set of instances, search solutions implemented, and the evaluation methods used to evaluate the proposed interaction solutions. From this review, we can conclude that researchers have started to deviate from more traditional visualisation techniques, like graph visualisations, when developing for lay users. This shows a current effort in developing Semantic Web tools to be used by lay users and motivates the documentation and formalisation of the solutions encountered in the studied tools. Copyright © 2021 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

Teses
supervisionadas

2021

Gestão de Frota - Visão 360º

Autor
Pedro Manuel Almeida Roseira

Instituição
UP-FEUP

2021

Sistema de Visão Termográfico para Veículos Autónomos Aéreos

Autor
CARLOS MANUEL DE SOUSA FERRÁS

Instituição
IPP-ISEP

2021

O PAPEL DA COMUNICAÇÃO PROMOCIONAL NAS COMPRAS POR IMPULSO DO CONTINENTE ONLINE

Autor
Ana Rita Pereira Mendes

Instituição
UP-FEP

2021

Modular Architecture for 3D Game Environment Art with Photogrammetry

Autor
Nataska Statham

Instituição
UP-FEUP

2021

Power Recycled Combiner for RF Wireless Transmitter

Autor
Bruno Miguel Gonçalves Saraiva

Instituição
UP-FEUP