In Brazil, citizens can report irregularities in the Public Administration. The classification of these complaints needs information that is not in their texts. this article aims is to propose a methodology for extracting and enriching information identified in complaints texts. This methodology provides as output a set of structured data capable of characterizing the complaints. To validate the proposal, a case study was done. The study showed that structured data use enabled an improvement in the performance of the complaint’s classification.

Extraction and enrichment of features to improve complaint text classification performance


 **Chairs:** Emerson Paraiso, Elaine Faria and Paulo T. Guerra 



Natural Language Processing I

technical paper

**BRACIS** originated from the combination of the two most important scientific events in Brazil in Artificial Intelligence (AI) and Computational Intelligence (CI): the Brazilian Symposium on Artificial Intelligence – **SBIA** (22 editions), and the Brazilian Symposium on Neural Networks – **SBRN** (13 editions). **ENIAC** is a national forum for researchers, practitioners, educators and students to present and discuss innovations, trends, experiences, developments and work in progress in the fields of Artificial and Computational Intelligence. **STIL** is the bi-annual Language Technology event.
All events are supported by the Brazilian Computer Society – Special Interest Groups: **CE-IA**, **CE-IC** and **CE-PLN**.

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BRACIS 2021

BRACIS originated from the combination of the two most important scientific events in Brazil in Artificial Intelligence (AI) and Computational Intelligence (CI): the Brazilian Symposium on Artificial Intelligence – SBIA (22 editions), and the Brazilian Symposium on Neural Networks – SBRN (13 editions). 
ENIAC is a national forum for researchers, practitioners, educators and students to present and discuss innovations, trends, experiences, developments and work in progress in the fields of Artificial and Computational Intelligence. 
STIL is the bi-annual Language Technology event.
All events are supported by the Brazilian Computer Society – Special Interest Groups: CE-IA, CE-IC and CE-PLN

Eduardo Paiva

1

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Extraction and enrichment of features to improve complaint text classification performance

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