Semantically enriched representations for Portuguese textmining: models and applications

• Grant number: 19/25010-5
• Support Opportunities: Regular Research Grants
• Start date: November 01, 2020
• End date: April 30, 2023
• Field of knowledge: Physical Sciences and Mathematics - Computer Science
• Principal Investigator: Solange Oliveira Rezende
• Grantee: Solange Oliveira Rezende
• Host Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
• City of the host institution: São Carlos
• Associated researchers: Alípio Mário Guedes Jorge ; Bruno Magalhães Nogueira ; Camila Vaccari Sundermann ; Marcos Aurelio Domingues ; Rafael Geraldeli Rossi ; Ricardo Marcondes Marcacini ; Roberta Akemi Sinoara ; Veronica Oliveira de Carvalho

Abstract

Text Mining techniques have become essential for supporting text analysis and knowledge discovery as the volume and variety of digital text documents have increased, either in social networks and the Web or inside organizations. Despite the application task or applied technique, the treatment of text semantics is an important challenge of the Text Mining process. The challenge is even bigger when we analyze Portuguese texts due to language particularities and the low number of Portuguese resources and researches. In this context, this project aims to advance Text Mining research, focusing on the Portuguese language, and disseminate the knowledge of the field by applying Text Mining techniques in different real-world problems. We will investigate and propose semantically enriched text representation models, considering both the vector-space model and network-based representations, as well as their application in one-class learning. As a first step to support this research, we will collect, prepare and characterize collections of texts written in Portuguese, and make consolidated information about labeled collections available to the research community. Lastly, we will evaluate and apply semantically enriched text representations in different Text Mining problems, such as sentiment analysis, recommendation systems, fake news detection, literature-based discovery and event mining. (AU)

Scientific publications

(20)

(The scientific publications listed on this page originate from the Web of Science or SciELO databases. Their authors have cited FAPESP grant or fellowship project numbers awarded to Principal Investigators or Fellowship Recipients, whether or not they are among the authors. This information is collected automatically and retrieved directly from those bibliometric databases.)

PEGORARO SANTANA, IGOR ANDRE; DOMINGUES, MARCOS AURELIO. CONTEXT-AWARE MUSIC RECOMMENDATION WITH METADATA AWARENESS AND RECURRENT NEURAL NETWORKS. COMPUTING AND INFORMATICS, v. 41, n. 3, p. 27-pg., 2022-01-01. (19/25010-5)

ARAUJO, ADAILTON F.; GOLO, MARCOS P. S.; MARCACINI, RICARDO M.. Opinion mining for app reviews: an analysis of textual representation and predictive models. AUTOMATED SOFTWARE ENGINEERING, v. 29, n. 1, MAY 2022. (19/25010-5, 19/07665-4)

RODRIGUES MATTOS, JOAO PEDRO; MARCACINI, RICARDO M.; BAILEY, J; MIETTINEN, P; KOH, YS; TAO, D; WU, X. Semi-Supervised Graph Attention Networks for Event Representation Learning. 2021 21ST IEEE INTERNATIONAL CONFERENCE ON DATA MINING (ICDM 2021), v. N/A, p. 6-pg., 2021-01-01. (19/25010-5, 19/07665-4)

ALVES DE LIMA, VITOR MESAQUE; DE ARAUJO, ADAILTON FERREIRA; MARCACINI, RICARDO MARCONDES. Temporal dynamics of requirements engineering from mobile app reviews. PEERJ COMPUTER SCIENCE, v. 7, p. 26-pg., 2022-03-15. (19/25010-5, 19/07665-4)

STEVE ATAUCURI CRUZ, LORD FLAUBERT; SILVA, DIEGO FURTADO; WANI, MA; SETHI, I; SHI, W; QU, G; RAICU, DS; JIN, R. Financial Time Series Forecasting Enriched with Textual Information. 20TH IEEE INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLICATIONS (ICMLA 2021), v. N/A, p. 6-pg., 2021-01-01. (19/25010-5)

GOLO, MARCOS P. S.; ARAUJO, ADAILTON F.; ROSSI, RAFAEL G.; MARCACINI, RICARDO M.. Detecting relevant app reviews for software evolution and maintenance through multimodal one-class learning. INFORMATION AND SOFTWARE TECHNOLOGY, v. 151, p. 12-pg., 2022-07-14. (19/25010-5)

GONZAGA, VICTOR MACHADO; MURRUGARRA-LLERENA, NILS; MARCACINI, RICARDO; ACM. Multimodal intent classification with incomplete modalities using text embedding propagation. PROCEEDINGS OF THE 27TH BRAZILIAN SYMPOSIUM ON MULTIMEDIA AND THE WEB (WEBMEDIA '21), v. N/A, p. 4-pg., 2021-01-01. (19/07665-4, 19/25010-5)

ALVES DE LIMA, VITOR MESAQUE; BARBOSA, JACSON RODRIGUES; MARCACINI, RICARDO MARCODES. iRisk: A Scalable Microservice for Classifying Issue Risks Based on Crowdsourced App Reviews. 2024 IEEE INTERNATIONAL CONFERENCE ON SOFTWARE MAINTENANCE AND EVOLUTION, ICSME 2024, v. N/A, p. 5-pg., 2024-01-01. (19/25010-5, 19/07665-4)

DOS REIS FILHO, IVAN JOSE; COLETI, JAMILLE DE CAMPOS; MARCACINI, RICARDO MARCONDES; REZENDE, SOLANGE OLIVEIRA. Dataset: Annotated soybean market news articles. DATA IN BRIEF, v. 55, p. 9-pg., 2024-06-08. (19/07665-4, 19/25010-5)

ALVES DE LIMA, VITOR MESAQUE; BARBOSA, JACSON RODRIGUES; MARCACINI, RICARDO MARCONDES. Monitoring Temporal Dynamics of Issues in Crowdsourced User Reviews and their Impact on Mobile App Updates. 2024 IEEE INTERNATIONAL CONFERENCE ON SOFTWARE MAINTENANCE AND EVOLUTION, ICSME 2024, v. N/A, p. 6-pg., 2024-01-01. (19/25010-5, 19/07665-4)

DO CARMO, PAULO; MARCACINI, RICARDO; CHEN, Y; LUDWIG, H; TU, Y; FAYYAD, U; ZHU, X; HU, X; BYNA, S; LIU, X; et al. Embedding propagation over heterogeneous event networks for link prediction. 2021 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA), v. N/A, p. 10-pg., 2021-01-01. (19/25010-5, 19/07665-4)

PEGORARO SANTANA, IGOR ANDRE; DOMINGUES, MARCOS AURELIO. Improving Context-Aware Music Recommender Systems with a Dual Recurrent Neural Network. INFORMATION MANAGEMENT AND BIG DATA, SIMBIG 2020, v. 1410, p. 11-pg., 2021-01-01. (19/25010-5)

DE LIMA, VITOR MESAQUE ALVES; BARBOSA, JACSON RODRIGUES; MARCACINI, RICARDO MARCONDES. Issue detection and prioritization based on mobile application reviews. SOFTWARE QUALITY JOURNAL, v. 33, n. 1, p. 35-pg., 2025-03-01. (19/07665-4, 19/25010-5)

DE SOUZA, MARIANA CARAVANTI; NOGUEIRA, BRUNO MAGALHAES; ROSSI, RAFAEL GERALDELI; MARCACINI, RICARDO MARCONDES; DOS SANTOS, BRUCCE NEVES; REZENDE, SOLANGE OLIVEIRA. A network-based positive and unlabeled learning approach for fake news detection. MACHINE LEARNING, NOV 2021. (19/25010-5)

REIS FILHO, IVAN J.; MARTINS, LUIZ H. D.; PARMEZAN, ANTONIO R. S.; MARCACINI, RICARDO M.; REZENDE, SOLANGE O.; XAVIER-JUNIOR, JC; RIOS, RA. Sequential Short-Text Classification from Multiple Textual Representations with Weak Supervision. INTELLIGENT SYSTEMS, PT I, v. 13653, p. 15-pg., 2022-01-01. (19/07665-4, 19/25010-5)

SANTOS, BRUCCE NEVES DOS; MARCACINI, RICARDO MARCONDES; REZENDE, SOLANGE OLIVEIRA. Multi-Domain Aspect Extraction Using Bidirectional Encoder Representations From Transformers. IEEE ACCESS, v. 9, p. 91604-91613, 2021. (19/25010-5, 19/07665-4)

GOLO, MARCOS PAULO SILVA; DE SOUZA, MARIANA CARAVANTI; ROSSI, RAFAEL GERALDELI; REZENDE, SOLANGE OLIVEIRA; NOGUEIRA, BRUNO MAGALHAES; MARCACINI, RICARDO MARCONDES. One-class learning for fake news detection through multimodal variational autoencoders. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, v. 122, p. 23-pg., 2023-03-11. (19/25010-5)

DE MORAES JUNIOR, MARCELO ISAIAS; MARCACINI, RICARDO MARCONDES; IEEE. On the Use of Aggregation Functions for Semi-Supervised Network Embedding. 2023 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, IJCNN, v. N/A, p. 8-pg., 2023-01-01. (22/09091-8, 19/25010-5, 19/07665-4)

FUJIMOTO, MAGALY LIKA; MARCACINI, RICARDO MARCONDES; REZENDE, SOLANGE OLIVEIRA. Scoping review of multimodal sentiment analysis and summarization: State of the art, challenges and future directions. Information Fusion, v. 130, p. 17-pg., 2026-06-01. (19/25010-5, 23/10100-4, 13/07375-0, 19/07665-4)

DE SOUZA, MARIANA CARAVANTI; GOLO, MARCOS PAULO SILVA; JORGE, ALIPIO MARIO GUEDES; DE AMORIM, EVELIN CARVALHO FREIRE; CAMPOS, RICARDO NUNO TABORDA; MARCACINI, RICARDO MARCONDES; REZENDE, SOLANGE OLIVEIRA. Keywords attention for fake news detection using few positive labels. INFORMATION SCIENCES, v. 663, p. 23-pg., 2024-02-14. (19/07665-4, 19/25010-5)