Active Mining pp 112-125 | Cite as

First-Order Rule Mining by Using Graphs Created from Temporal Medical Data

  • Ryutaro Ichise
  • Masayuki Numao
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3430)


In managing medical data, handling time-series data, which contain irregularities, presents the greatest difficulty. In the present paper, we propose a first-order rule discovery method for handling such data. The present method is an attempt to use graph structure to represent time-series data and reduce the graph using specified rules for inducing hypothesis. In order to evaluate the proposed method, we conducted experiments using real-world medical data.


Medical Data Dynamic Time Warping Interferon Therapy Inductive Logic Programming Horn Clause 
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 2005

Authors and Affiliations

  • Ryutaro Ichise
    • 1
  • Masayuki Numao
    • 2
  1. 1.Intelligent Systems Research DivisionNational Institute of InformaticsTokyoJapan
  2. 2.The Institute of Scientific and Industrial ResearchOsaka UniversityOsakaJapan

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