6 Search Results for "Rodrigues, Mário"

Document
DOI: 10.4230/OASIcs.SLATE.2023.2
A Framework for Fostering Easier Access to Enriched Textual Information

Authors: Gabriel Silva, Mário Rodrigues, António Teixeira, and Marlene Amorim

Published in: OASIcs, Volume 113, 12th Symposium on Languages, Applications and Technologies (SLATE 2023)

Abstract
Considering the amount of information in unstructured data it is necessary to have suitable methods to extract information from it. Most of these methods have their own output making it difficult and costly to merge and share this information as there currently is no unified way of representing this information. While most of these methods rely on JSON or XML there has been a push to serialize these into RDF compliant formats due to their flexiblity and the existing ecosystem surrounding them. In this paper we introduce a framework whose goal is to provide a serialization of enriched data into an RDF format, following FAIR principles, making it more interpretable, interoperable and shareable. We process a subset of the WikiNER dataset and showcase two examples of using this framework: One using CoNLL annotations and the other by performing entity-linking on an already existing graph. The results are a graph with every connection starting from the document and finishing on tokens while keeping the original text intact while embedding the enriched data into it, in this case the CoNLL annotations and Entities.
Cite as

Gabriel Silva, Mário Rodrigues, António Teixeira, and Marlene Amorim. A Framework for Fostering Easier Access to Enriched Textual Information. In 12th Symposium on Languages, Applications and Technologies (SLATE 2023). Open Access Series in Informatics (OASIcs), Volume 113, pp. 2:1-2:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{silva_et_al:OASIcs.SLATE.2023.2,
  author =	{Silva, Gabriel and Rodrigues, M\'{a}rio and Teixeira, Ant\'{o}nio and Amorim, Marlene},
  title =	{{A Framework for Fostering Easier Access to Enriched Textual Information}},
  booktitle =	{12th Symposium on Languages, Applications and Technologies (SLATE 2023)},
  pages =	{2:1--2:14},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-291-4},
  ISSN =	{2190-6807},
  year =	{2023},
  volume =	{113},
  editor =	{Sim\~{o}es, Alberto and Ber\'{o}n, Mario Marcelo and Portela, Filipe},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2023.2},
  URN =		{urn:nbn:de:0030-drops-185165},
  doi =		{10.4230/OASIcs.SLATE.2023.2},
  annote =	{Keywords: Knowledge graphs, Enriched data, Natural language processing, Triplestore}
}
Document
DOI: 10.4230/OASIcs.SLATE.2023.5
Web of Science Citation Gaps: An Automatic Approach to Detect Indexed but Missing Citations

Authors: David Rodrigues, António L. Lopes, and Fernando Batista

Published in: OASIcs, Volume 113, 12th Symposium on Languages, Applications and Technologies (SLATE 2023)

Abstract
The number of citations a research paper receives is a crucial metric for both researchers and institutions. However, since citation databases have their own source lists, finding all the citations of a given paper can be a challenge. As a result, there may be missing citations that are not counted towards a paper’s total citation count. To address this issue, we present an automated approach to find missing citations leveraging the use of multiple indexing databases. In this research, Web of Science (WoS) serves as a case study and OpenAlex is used as a reference point for comparison. For a given paper, we identify all citing papers found in both research databases. Then, for each citing paper we check if it is indexed in WoS, but not referred in WoS as a citing paper, in order to determine if it is a missing citation. In our experiments, from a set of 1539 papers indexed by WoS, we found 696 missing citations. This outcome proves the success of our approach, and reveals that WoS does not always consider the full list of citing papers of a given publication, even when these citing papers are indexed by WoS. We also found that WoS has a higher chance of missing information for more recent publications. These findings provide relevant insights about this indexing research database, and provide enough motivation for considering other research databases in our study, such as Scopus and Google Scholar, in order to improve the matching and querying algorithms, and to reduce false positives, towards providing a more comprehensive and accurate view of the citations of a paper.
Cite as

David Rodrigues, António L. Lopes, and Fernando Batista. Web of Science Citation Gaps: An Automatic Approach to Detect Indexed but Missing Citations. In 12th Symposium on Languages, Applications and Technologies (SLATE 2023). Open Access Series in Informatics (OASIcs), Volume 113, pp. 5:1-5:11, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{rodrigues_et_al:OASIcs.SLATE.2023.5,
  author =	{Rodrigues, David and Lopes, Ant\'{o}nio L. and Batista, Fernando},
  title =	{{Web of Science Citation Gaps: An Automatic Approach to Detect Indexed but Missing Citations}},
  booktitle =	{12th Symposium on Languages, Applications and Technologies (SLATE 2023)},
  pages =	{5:1--5:11},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-291-4},
  ISSN =	{2190-6807},
  year =	{2023},
  volume =	{113},
  editor =	{Sim\~{o}es, Alberto and Ber\'{o}n, Mario Marcelo and Portela, Filipe},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2023.5},
  URN =		{urn:nbn:de:0030-drops-185199},
  doi =		{10.4230/OASIcs.SLATE.2023.5},
  annote =	{Keywords: Research Databases, Citations, Citation Databases, Web of Science, OpenAlex}
}
Document
DOI: 10.4230/OASIcs.SLATE.2023.8
OCRticle - a Structure-Aware OCR Application

Authors: Sofia G. Rodrigues dos Santos and J. João Dias de Almeida

Published in: OASIcs, Volume 113, 12th Symposium on Languages, Applications and Technologies (SLATE 2023)

Abstract
While there are currently many applications and websites capable of performing Optical Character Recognition (OCR), none of the widely available options offer structured OCR, i.e., OCR that maintains the text’s original structure. For example, if a document has a title, after performing OCR on it, the title should have a different formatting, in order to distinguish it from the rest of the text. This paper covers the topic of structure-aware OCR, first by describing the current state of OCR tools, then by showcasing a prototype tool capable of retaining the structure of articles scanned from an image.
Cite as

Sofia G. Rodrigues dos Santos and J. João Dias de Almeida. OCRticle - a Structure-Aware OCR Application. In 12th Symposium on Languages, Applications and Technologies (SLATE 2023). Open Access Series in Informatics (OASIcs), Volume 113, pp. 8:1-8:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{rodriguesdossantos_et_al:OASIcs.SLATE.2023.8,
  author =	{Rodrigues dos Santos, Sofia G. and Dias de Almeida, J. Jo\~{a}o},
  title =	{{OCRticle - a Structure-Aware OCR Application}},
  booktitle =	{12th Symposium on Languages, Applications and Technologies (SLATE 2023)},
  pages =	{8:1--8:14},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-291-4},
  ISSN =	{2190-6807},
  year =	{2023},
  volume =	{113},
  editor =	{Sim\~{o}es, Alberto and Ber\'{o}n, Mario Marcelo and Portela, Filipe},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2023.8},
  URN =		{urn:nbn:de:0030-drops-185220},
  doi =		{10.4230/OASIcs.SLATE.2023.8},
  annote =	{Keywords: OCR, Optical Character Recognition, Data Structure, Data Parsing, Document Structure}
}
Document
DOI: 10.4230/OASIcs.SLATE.2021.11
Towards Automatic Creation of Annotations to Foster Development of Named Entity Recognizers

Authors: Emanuel Matos, Mário Rodrigues, Pedro Miguel, and António Teixeira

Published in: OASIcs, Volume 94, 10th Symposium on Languages, Applications and Technologies (SLATE 2021)

Abstract
Named Entity Recognition (NER) is an essential step for many natural language processing tasks, including Information Extraction. Despite recent advances, particularly using deep learning techniques, the creation of accurate named entity recognizers continues a complex task, highly dependent on annotated data availability. To foster existence of NER systems for new domains it is crucial to obtain the required large volumes of annotated data with low or no manual labor. In this paper it is proposed a system to create the annotated data automatically, by resorting to a set of existing NERs and information sources (DBpedia). The approach was tested with documents of the Tourism domain. Distinct methods were applied for deciding the final named entities and respective tags. The results show that this approach can increase the confidence on annotations and/or augment the number of categories possible to annotate. This paper also presents examples of new NERs that can be rapidly created with the obtained annotated data. The annotated data, combined with the possibility to apply both the ensemble of NER systems and the new Gazetteer-based NERs to large corpora, create the necessary conditions to explore the recent neural deep learning state-of-art approaches to NER (ex: BERT) in domains with scarce or nonexistent data for training.
Cite as

Emanuel Matos, Mário Rodrigues, Pedro Miguel, and António Teixeira. Towards Automatic Creation of Annotations to Foster Development of Named Entity Recognizers. In 10th Symposium on Languages, Applications and Technologies (SLATE 2021). Open Access Series in Informatics (OASIcs), Volume 94, pp. 11:1-11:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{matos_et_al:OASIcs.SLATE.2021.11,
  author =	{Matos, Emanuel and Rodrigues, M\'{a}rio and Miguel, Pedro and Teixeira, Ant\'{o}nio},
  title =	{{Towards Automatic Creation of Annotations to Foster Development of Named Entity Recognizers}},
  booktitle =	{10th Symposium on Languages, Applications and Technologies (SLATE 2021)},
  pages =	{11:1--11:14},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-202-0},
  ISSN =	{2190-6807},
  year =	{2021},
  volume =	{94},
  editor =	{Queir\'{o}s, Ricardo and Pinto, M\'{a}rio and Sim\~{o}es, Alberto and Portela, Filipe and Pereira, Maria Jo\~{a}o},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2021.11},
  URN =		{urn:nbn:de:0030-drops-144286},
  doi =		{10.4230/OASIcs.SLATE.2021.11},
  annote =	{Keywords: Named Entity Recognition (NER), Automatic Annotation, Gazetteers, Tourism, Portuguese}
}
Document
DOI: 10.4230/OASIcs.SLATE.2019.13
Knowledge Representation of Crime-Related Events: a Preliminary Approach

Authors: Gonçalo Carnaz, Vitor Beires Nogueira, and Mário Antunes

Published in: OASIcs, Volume 74, 8th Symposium on Languages, Applications and Technologies (SLATE 2019)

Abstract
The crime is spread in every daily newspaper, and particularly on criminal investigation reports produced by several Police departments, creating an amount of data to be processed by Humans. Other research studies related to relation extraction (a branch of information retrieval) in Portuguese arisen along the years, but with few extracted relations and several computer methods approaches, that could be improved by recent features, to achieve better performance results. This paper aims to present the ongoing work related to SEM (Simple Event Model) ontology population with instances retrieved from crime-related documents, supported by an SVO (Subject, Verb, Object) algorithm using hand-crafted rules to extract events, achieving a performance measure of 0.86 (F-Measure).
Cite as

Gonçalo Carnaz, Vitor Beires Nogueira, and Mário Antunes. Knowledge Representation of Crime-Related Events: a Preliminary Approach. In 8th Symposium on Languages, Applications and Technologies (SLATE 2019). Open Access Series in Informatics (OASIcs), Volume 74, pp. 13:1-13:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{carnaz_et_al:OASIcs.SLATE.2019.13,
  author =	{Carnaz, Gon\c{c}alo and Nogueira, Vitor Beires and Antunes, M\'{a}rio},
  title =	{{Knowledge Representation of Crime-Related Events: a Preliminary Approach}},
  booktitle =	{8th Symposium on Languages, Applications and Technologies (SLATE 2019)},
  pages =	{13:1--13:8},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-114-6},
  ISSN =	{2190-6807},
  year =	{2019},
  volume =	{74},
  editor =	{Rodrigues, Ricardo and Janou\v{s}ek, Jan and Ferreira, Lu{\'\i}s and Coheur, Lu{\'\i}sa and Batista, Fernando and Gon\c{c}alo Oliveira, Hugo},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2019.13},
  URN =		{urn:nbn:de:0030-drops-108809},
  doi =		{10.4230/OASIcs.SLATE.2019.13},
  annote =	{Keywords: SEM Ontology, Relation Extraction, Crime-Related Events, SVO Algorithm, Ontology Population}
}
Document
DOI: 10.4230/OASIcs.SLATE.2017.20
Natural Transmission of Information Extraction Results to End-Users - A Proof-of-Concept Using Data-to-Text

Authors: José Casimiro Pereira, António J. S. Teixeira, Mário Rodrigues, Pedro Miguel, and Joaquim Sousa Pinto

Published in: OASIcs, Volume 56, 6th Symposium on Languages, Applications and Technologies (SLATE 2017)

Abstract
Information Extraction from natural texts has a great potential in areas such as Tourism and can be of great assistance in transforming customers' comments in valuable information for Tourism operators, governments and customers. After extraction, information needs to be efficiently transmitted to end-users in a natural way. Systems should not, in general, send extracted information directly to end-users, such as hotel managers, as it can be difficult to read. Naturally, humans transmit and encode information using natural languages, such as Portuguese. The problem arising from the need of efficient and natural transmission of the information to end-user is how to encode it. The use of natural language generation (NLG) is a possible solution, for producing sentences, and, with them, texts. In this paper we address this, with a data-to-text system, a derivation of formal NLG systems that use data as input. The proposed system uses an aligned corpus, which was defined, collected and processed, in about approximately 3 weeks of work. To build the language model were used three different in-domain and out-of-domain corpora. The effects of this approach were evaluated, and results are presented. Automatic metrics, BLEU and Meteor, were used to evaluate the different systems, comparing their values with similar systems. Results show that expanding the corpus has a major positive effect in BLEU and Meteor scores and use of additional corpora (in-domain and out-of-domain) in training language model does not result in significantly different performance. The scores obtained, combined with their comparison with other systems performance and informal evaluation by humans of the sentences produced, give additional support for the capabilities of the translation based approach for fast development of data-to-text for new domains.
Cite as

José Casimiro Pereira, António J. S. Teixeira, Mário Rodrigues, Pedro Miguel, and Joaquim Sousa Pinto. Natural Transmission of Information Extraction Results to End-Users - A Proof-of-Concept Using Data-to-Text. In 6th Symposium on Languages, Applications and Technologies (SLATE 2017). Open Access Series in Informatics (OASIcs), Volume 56, pp. 20:1-20:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)

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@InProceedings{pereira_et_al:OASIcs.SLATE.2017.20,
  author =	{Pereira, Jos\'{e} Casimiro and Teixeira, Ant\'{o}nio J. S. and Rodrigues, M\'{a}rio and Miguel, Pedro and Pinto, Joaquim Sousa},
  title =	{{Natural Transmission of Information Extraction Results to End-Users - A Proof-of-Concept Using Data-to-Text}},
  booktitle =	{6th Symposium on Languages, Applications and Technologies (SLATE 2017)},
  pages =	{20:1--20:14},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-056-9},
  ISSN =	{2190-6807},
  year =	{2017},
  volume =	{56},
  editor =	{Queir\'{o}s, Ricardo and Pinto, M\'{a}rio and Sim\~{o}es, Alberto and Leal, Jos\'{e} Paulo and Varanda, Maria Jo\~{a}o},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2017.20},
  URN =		{urn:nbn:de:0030-drops-79530},
  doi =		{10.4230/OASIcs.SLATE.2017.20},
  annote =	{Keywords: Data-to-Text, Natural Language Generation, Automatic Translation, opinions, Tourism, Portuguese}
}
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