A proposal for an architecture to extract information from sms messages during emergency situations

• Ano de defesa: 2015
• Autor(a) principal: Monteiro, Douglas Machado
• Orientador(a): Lima, Vera Lúcia Strube de
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Pontifícia Universidade Católica do Rio Grande do Sul
• Programa de Pós-Graduação: Programa de Pós-Graduação em Ciência da Computação
• Departamento: Faculdade de Informática
• País: Brasil
• Palavras-chave em Português: INFORMÁTICA; PROCESSAMENTO DA LINGUAGEM NATURAL; RECUPERAÇÃO DA INFORMAÇÃO
• Área do conhecimento CNPq: CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
• Link de acesso: http://tede2.pucrs.br/tede2/handle/tede/6013

In mass emergencies, a fair amount of information is exchanged via SMS messages. These messages tend to be informal and to contain abbreviations and misspellings, which makes them difficult to treat. This is a problem for current Information Extraction tools, especially for messages in Portuguese. This work proposes an architecture to extract information from SMS messages during emergencies. The architecture comprises four components: Linguistic Processing, Temporal Processing, Event Processing, and Information Fusion. We also defined an SMS corpus building process. From the proposal of this architecture, we conducted a case study, which included building BraCorpSMS, a corpus of SMS messages received by an electric utility company. We built a prototype in Python using NLTK to validate the architecture. The prototype had its Information Extraction components evaluated achieving Precision of 88%, Recall of 59% and balanced F-measure of 71%. The results indicate improvement opportunities, but as this is the first work for Portuguese facing processing SMS messages during emergency situations, it also serves as a roadmap for future work in the area.