Active Mining pp 112-125

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

  • Ryutaro Ichise
  • Masayuki Numao
Conference paper

DOI: 10.1007/11423270_7

Part of the Lecture Notes in Computer Science book series (LNCS, volume 3430)
Cite this paper as:
Ichise R., Numao M. (2005) First-Order Rule Mining by Using Graphs Created from Temporal Medical Data. In: Tsumoto S., Yamaguchi T., Numao M., Motoda H. (eds) Active Mining. Lecture Notes in Computer Science, vol 3430. Springer, Berlin, Heidelberg

Abstract

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.

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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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