A Distance-Based Approach to Find Interesting Patterns

  • Chen Zheng
  • Yanfen Zhao
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2737)


One of the major problems in knowledge discovery is producing too many trivial and uninteresting patterns. The measurement of interestingness is divided into subjective and objective measures and used to address the problem. In this paper, we propose a novel method to discover interesting patterns by incorporating the domain user’s preconceived knowledge. The prior knowledge constitutes a set of hypothesis about the domain. A new parameter called the distance is proposed to measure the gap between the user’s existing hypothesis and system-generated knowledge. To evaluate the practicality of our approach, we apply the proposed approach through some real-life data sets and present our findings.


Fuzzy Rule Linguistic Term Interesting Pattern Attribute Weight Antecedent Part 
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 2003

Authors and Affiliations

  • Chen Zheng
    • 1
  • Yanfen Zhao
    • 2
  1. 1.Department of Computer ScienceNational University of SingaporeSingapore
  2. 2.China Construction BankFujianP.R.China

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