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International Joint Conference SOCO’13-CISIS’13-ICEUTE’13 pp 211–220Cite as

Text Classification Techniques in Oil Industry Applications

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 239))

Abstract

The development of automatic methods to produce usable structured information from unstructured text sources is extremely valuable to the oil and gas industry. A structured resource would allow researches and industry professionals to write relatively simple queries to retrieve all the information regards transcriptions of any accident. Instead of the thousands of abstracts provided by querying the unstructured corpus, the queries on structured corpus would result in a few hundred well-formed results.

On this paper we propose and evaluate information extraction techniques in occupational health control process, particularly, for the case of automatic detection of accidents from unstructured texts. Our proposal divides the problem in subtasks such as text analysis, recognition and classification of failed occupational health control, resolving accidents.

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Author information

Authors and Affiliations

  1. ADDLabs, Fluminense Federal University, Rua Passo da Pátria, 156., 24210-240, Niterói, RJ, Brazil

    Nayat Sanchez-Pi & Ana Cristina Bicharra Garcia

  2. Dept. of Electrical Engineering, Pontifícia Universidade Católica do Rio de Janeiro, R. Marquês de São Vicente, 225., Rio de Janeiro, RJ, Brazil

    Luis Martí

Authors
  1. Nayat Sanchez-Pi
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  2. Luis Martí
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  3. Ana Cristina Bicharra Garcia
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Corresponding author

Correspondence to Nayat Sanchez-Pi .

Editor information

Editors and Affiliations

  1. Department of Civil Engineering, University of Burgos, Burgos, Spain

    Álvaro Herrero

  2. Department of Civil Engineering, University of Burgos, Burgos, Spain

    Bruno Baruque

  3. German Workforce ADL Partnership Laboratory, Waltershausen, Germany

    Fanny Klett

  4. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR Labs), Auburn, Washington, USA

    Ajith Abraham

  5. Department of Computer Science Faculty of Ele. Eng. & Computer Science, VŠB-TU Ostrava, Ostrava, Czech Republic

    Václav Snášel

  6. Department of Computer Science, University of Sao Paulo at Sao Carlos, Sao Carlos, Brazil

    André C.P.L.F. de Carvalho

  7. DeustoTech Computing, University of Deusto, Bilbao, Spain

    Pablo García Bringas

  8. Department of Computer Science Faculty of Elec. Eng. and Comp. Science, VŠB-TU Ostrava, Ostrava, Czech Republic

    Ivan Zelinka

  9. University of Salamanca, Salamanca, Spain

    Héctor Quintián

  10. University of Salamanca, Salamanca, Spain

    Emilio Corchado

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© 2014 Springer International Publishing Switzerland

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Sanchez-Pi, N., Martí, L., Garcia, A.C.B. (2014). Text Classification Techniques in Oil Industry Applications. In: Herrero, Á., et al. International Joint Conference SOCO’13-CISIS’13-ICEUTE’13. Advances in Intelligent Systems and Computing, vol 239. Springer, Cham. https://doi.org/10.1007/978-3-319-01854-6_22

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  • DOI: https://doi.org/10.1007/978-3-319-01854-6_22

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-01853-9

  • Online ISBN: 978-3-319-01854-6

  • eBook Packages: EngineeringEngineering (R0)

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