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About

Sérgio Nunes is an Assistant 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).

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.

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 Masters, and the Multimedia Masters.

Interest
Topics
Details

Details

004
Publications

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

2021

Managing research the wiki way

Authors
Devezas, JL; Nunes, S;

Publication
XRDS

Abstract

2021

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

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

Publication
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

Authors
Devezas, J; Nunes, S;

Publication
SN Computer Science

Abstract

2021

A Survey on User Interaction with Linked Data

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

Publication
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).

Supervised
thesis

2021

Power Recycled Combiner for RF Wireless Transmitter

Author
Bruno Miguel Gonçalves Saraiva

Institution
UP-FEUP

2021

Community-based Sports Articles Generation Platform using NLG and Post-Editing

Author
Pedro Miguel Sousa Fernandes

Institution
UP-FEUP

2021

User Interaction Patterns for Linked Data

Author
Mariana Barbosa Aguiar

Institution
UP-FEUP

2021

Narrative Visualization of News Stories

Author
Mariana Filipa da Costa

Institution
UP-FEUP

2021

A platform for monitoring search performance

Author
Ricardo Araújo Bóia

Institution
UP-FEUP