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Semantic Representation for Text Classification

Grant number: 16/07620-2
Support type:Scholarships abroad - Research Internship - Doctorate
Effective date (Start): August 01, 2016
Effective date (End): January 31, 2017
Field of knowledge:Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
Principal Investigator:Solange Oliveira Rezende
Grantee:Roberta Akemi Sinoara
Supervisor abroad: Roberto Navigli
Home Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
Local de pesquisa : Università degli Studi di Roma La Sapienza, Italy  
Associated to the scholarship:13/14757-6 - Incorporating the semantics into the websensors construction process, BP.DR

Abstract

In text mining, traditional text representation are based on the frequency of words in the documents. Although good results for automatic text classification can be achieved with the use of this bag-of-words representation, such representation model is not suitable for all classification problems and richer text representations can be required. The objective of this internship project is to develop a semantic text representation based on NASARI approach. NASARI is a concept representation used to measure semantic similarity with good results in word similarity and sense clustering tasks. It is based on knowledge from both WordNet and Wikipedia. Thus, this project aims to enhance document representation with the semantically rich NASARI concept representation. The proposed text representation will be evaluated in text classification tasks. It is expected that the use of a NASARI-based text representation will improve text classification performance. This project is closely related to the student's doctoral project in development at Universidade de São Paulo. The internship project will be developed at Sapienza - Università di Roma, under the supervision of professor Roberto Navigli, who is one of the authors of NASARI approach.

News published in Agência FAPESP Newsletter about the scholarship:
Artificial intelligence to track news of COVID-19 
Articles published in other media outlets (14 total):
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Radar do Futuro: Inteligência artificial rastreia notícias sobre a pandemia (23/Apr/2020)
Portal Banda B: Inteligência artificial rastreia notícias sobre curvas de contágio do Covid-19 no Brasil (13/Apr/2020)
Aroldo Murá: INTELIGÊNCIA ARTIFICIAL RASTREIA NOTÍCIAS CURVAS DE CONTÁGIO DO COVID-19 NO BRASIL (09/Apr/2020)
Mundo e Meio: Inteligência artificial rastreia notícias do covid-19 no mundo (08/Apr/2020)
TN Petróleo online: Inteligência artificial rastreia notícias sobre COVID-19 (07/Apr/2020)
JC Notícias (São Paulo, SP): Inteligência artificial rastreia notícias sobre covid-19 (07/Apr/2020)
Biblioteca FMUSP: Websensors, está sendo utilizada na análise da evolução da pandemia de COVID-19 (07/Apr/2020)
Tá Sabendo?: Inteligência artificial rastreia notícias sobre COVID-19 (07/Apr/2020)
Portal Neo Mondo: Inteligência artificial rastreia notícias sobre COVID-19 (07/Apr/2020)
ABIPTI - Associação Brasileira das Instituições de Pesquisa Tecnológica e Inovação: Inteligência artificial rastreia notícias sobre COVID-19 (07/Apr/2020)
Digital Rádio e TV: Inteligência artificial rastreia notícias sobre COVID-19 (07/Apr/2020)
Programa InfoSalud (Argentina): Inteligencia artificial rastrea noticias sobre Covid-19 (07/Apr/2020)
Blog A Crítica: Inteligência artificial rastreia notícias sobre COVID-19 (07/Apr/2020)
Na Cuia da Cris: Inteligência artificial rastreia notícias sobre COVID-19 (07/Apr/2020)

Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
SINOARA, ROBERTA A.; CAMACHO-COLLADOS, JOSE; ROSSI, RAFAEL G.; NAVIGLI, ROBERTO; REZENDE, SOLANGE O. Knowledge-enhanced document embeddings for text classification. KNOWLEDGE-BASED SYSTEMS, v. 163, p. 955-971, JAN 1 2019. Web of Science Citations: 4.

Please report errors in scientific publications list by writing to: cdi@fapesp.br.