Mobile-Based Emergency Response System Using Ontology-Supported Information Extraction

  • Khaled Amailef
  • Jie Lu
Part of the Intelligent Systems Reference Library book series (ISRL, volume 33)


This chapter describes an algorithm within a Mobile-based Emergency Response System (MERS) to automatically extract information from Short Message Service (SMS). The algorithm is based on an ontology concept, and a maximum entropy statistical model. Ontology has been used to improve the performance of an information extraction system. A maximum entropy statistical model with various predefined features offers a clean way to estimate the probability of certain token occurring with a certain SMS text. The algorithm has four main functions: to collect unstructured information from an SMS emergency text message; to conduct information extraction and aggregation; to calculate the similarity of SMS text messages; and to generate query and results presentation.


Mobile User Text Message Information Extraction Disaster Event Name Entity Recognition 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Khaled Amailef
    • 1
  • Jie Lu
    • 1
  1. 1.Decision Systems & e-Service Intelligence (DeSI) Lab, Centre for Quantum Computation & Intelligent Systems (QCIS), School of Software, Faculty of Engineering and Information TechnologyUniversity of Technology SydneySydneyAustralia

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