Semantic Tracking in Peer-to-Peer Topic Maps Management

  • Asanee Kawtrakul
  • Chaiyakorn Yingsaeree
  • Frederic Andres
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4777)


This paper presents a collaborative semantic tracking framework based on topic maps which aims to integrate and organize the data/information resources that spread throughout the Internet in the manner that makes them useful for tracking events such as natural disaster, and disease dispersion. We present the architecture we defined in order to support highly relevant semantic management and to provide adaptive services such as statistical information extraction technique for document summarization. In addition, this paper also carries out a case study on disease dispersion domain using the proposed framework.


Avian Influenza Natural Language Processing Information Extraction Distribute Hash Table 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 2007

Authors and Affiliations

  • Asanee Kawtrakul
    • 1
  • Chaiyakorn Yingsaeree
    • 1
  • Frederic Andres
    • 2
  1. 1.NAiST Research Laboratory, Kasetsart University, BangkokThailand
  2. 2.National Institute of Informatics, TokyoJapan

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