On the Support of a Similarity-enabled Relational Database Management System in Civilian Crisis Situations

Paulo H. Oliveira, Antonio C. Fraideinberze, Natan A. Laverde, Hugo Gualdron, Andre S. Gonzaga, Lucas D. Ferreira, Willian D. Oliveira, Jose F. Rodrigues-Jr., Robson L. F. Cordeiro, Caetano Traina Jr., Agma J. M. Traina, Elaine P. M. Sousa

2016

Abstract

Crowdsourcing solutions can be helpful to extract information from disaster-related data during crisis management. However, certain information can only be obtained through similarity operations. Some of them also depend on additional data stored in a Relational Database Management System (RDBMS). In this context, several works focus on crisis management supported by data. Nevertheless, none of them provide a methodology for employing a similarity-enabled RDBMS in disaster-relief tasks. To fill this gap, we introduce a methodology together with the Data-Centric Crisis Management (DCCM) architecture, which employs our methods over a similarity-enabled RDBMS. We evaluate our proposal through three tasks: classification of incoming data regarding current events, identifying relevant information to guide rescue teams; filtering of incoming data, enhancing the decision support by removing near-duplicate data; and similarity retrieval of historical data, supporting analytical comprehension of the crisis context. To make it possible, similarity-based operations were implemented within one popular, open-source RDBMS. Results using real data from Flickr show that our proposal is feasible for real-time applications. In addition to high performance, accurate results were obtained with a proper combination of techniques for each task. Hence, we expect our work to provide a framework for further developments on crisis management solutions.

References

  1. Aha, D., Kibler, D., and Albert, M. (1991). Instance-based learning algorithms. Machine Learning.
  2. Barioni, M., Kaster, D., Razente, H., Traina, A., and Traina Jr., C. (2011). Querying Multimedia Data by Similarity in Relational DBMS. In Advanced Database Query Systems.
  3. Bedo, M., Blanco, G., Oliveira, W., Cazzolato, M., Costa, A., Rodrigues Jr., J., Traina, A., and Traina Jr., C. (2015). Techniques for effective and efficient fire detection from social media images. ICEIS 7815.
  4. Bedo, M., Traina, A., and Traina Jr., C. (2014). Seamless integration of distance functions and feature vectors for similarity-queries processing. JIDM.
  5. Celik, T., Ozkaramanli, H., and Demirel, H. (2007). Fire and smoke detection without sensors: Image processing based approach. EUSIPCO 7807.
  6. Fix, E. and Hodges Jr., J. (1951). Discriminatory analysis - Nonparametric discrimination: Consistency properties. Technical report, DTIC Document.
  7. Ghahremanlou, L., Sherchan, W., and Thom, J. (2015). Geotagging Twitter messages in crisis management. The Computer Journal.
  8. Gibson, H., Andrews, S., Domdouzis, K., Hirsch, L., and Akhgar, B. (2014). Combining big social media data and FCA for crisis response. UCC 7814.
  9. Halder, B. (2014). Crowdsourcing collection of data for crisis governance in the post-2015 world: Potential offers and crucial challenges. ICEGOV 7814.
  10. Hamming, R. W. (1950). Error detecting and error correcting codes. Bell System Technical Journal.
  11. Huang, M., Smilowitz, K., and Balcik, B. (2013). A continuous approximation approach for assessment routing in disaster relief. Transportation Research Part B.
  12. Kaster, D., Bugatti, P., Ponciano-Silva, M., Traina, A., Marques, P., Santos, A., and Traina Jr., C. (2011). MedFMI-SiR: A powerful DBMS solution for largescale medical image retrieval. ITBAM 7811.
  13. Kudyba, S. (2014). Big Data, Mining, and Analytics: Components of Strategic Decision Making.
  14. Mehrotra, S., Butts, C., Kalashnikov, D., Venkatasubramanian, N., Rao, R., Chockalingam, G., Eguchi, R., Adams, B., and Huyck, C. (2004). Project Rescue: Challenges in responding to the unexpected. EI 7804.
  15. MultiMedia, I. (2002). MPEG-7: The generic multimedia content description standard, p. 1. IEEE MultiMedia.
  16. Reznik, T., Horakova, B., and Szturc, R. (2015). Advanced methods of cell phone localization for crisis and emergency management applications. IJDE.
  17. Sikora, T. (2001). The MPEG-7 visual standard for content description - An overview. IEEE Trans. Cir. Sys. Vid.
  18. Silva, Y., Aly, A., Aref, W., and Larson, P. (2010). SimDB: A similarity-aware database system. SIGMOD 7810.
  19. Wilson, D. and Martinez, T. (1997). Improved heterogeneous distance functions. J. Artif. Int. Res.
  20. Zhang, J., Li, J., and Liu, Z. (2012). Multiple-resource and multiple-depot emergency response problem considering secondary disasters. Expert Syst. Appl.
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Paper Citation


in Harvard Style

Oliveira P., Fraideinberze A., Laverde N., Gualdron H., Gonzaga A., Ferreira L., Oliveira W., Rodrigues-Jr. J., Cordeiro R., Traina Jr. C., Traina A. and Sousa E. (2016). On the Support of a Similarity-enabled Relational Database Management System in Civilian Crisis Situations . In Proceedings of the 18th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-187-8, pages 119-126. DOI: 10.5220/0005816701190126


in Bibtex Style

@conference{iceis16,
author={Paulo H. Oliveira and Antonio C. Fraideinberze and Natan A. Laverde and Hugo Gualdron and Andre S. Gonzaga and Lucas D. Ferreira and Willian D. Oliveira and Jose F. Rodrigues-Jr. and Robson L. F. Cordeiro and Caetano Traina Jr. and Agma J. M. Traina and Elaine P. M. Sousa},
title={On the Support of a Similarity-enabled Relational Database Management System in Civilian Crisis Situations},
booktitle={Proceedings of the 18th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2016},
pages={119-126},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005816701190126},
isbn={978-989-758-187-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 18th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - On the Support of a Similarity-enabled Relational Database Management System in Civilian Crisis Situations
SN - 978-989-758-187-8
AU - Oliveira P.
AU - Fraideinberze A.
AU - Laverde N.
AU - Gualdron H.
AU - Gonzaga A.
AU - Ferreira L.
AU - Oliveira W.
AU - Rodrigues-Jr. J.
AU - Cordeiro R.
AU - Traina Jr. C.
AU - Traina A.
AU - Sousa E.
PY - 2016
SP - 119
EP - 126
DO - 10.5220/0005816701190126