Probabilistic Logic-based Characterization of Knowledge Discovery in Databases

@inproceedings{Xie2002ProbabilisticLC,
  title={Probabilistic Logic-based Characterization of Knowledge Discovery in Databases},
  author={Ying Xie and Vijay V. Raghavan},
  year={2002}
}
From the perspective of knowledge representation and reasoning as well as for the automation of the knowledge discovery process, we argue that a formal logical foundation is needed for KDD and suggest Bacchus’ probability logic is a good choice. It is generally accepted that the unique and most important feature of a KDD system lies in its ability to discover previously unknown and potentially useful patterns. Therefore we give a formal definition of “pattern” as well as its determiners, which… CONTINUE READING

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Showing 1-10 of 11 references

Modeling the Real World for Data Mining: Granular Computer Approach

  • T. Y. Lin, Eric Louie
  • Proc. of IFSA/ NAFIPS
  • 2001
Highly Influential
4 Excerpts

Semantics Oriented Association Rules

  • Eric Louie, T. Y. Lin
  • Proc. of FUZZ-IEEE Conf.-2002 IEEE World Congress…
  • 2002
3 Excerpts

Rough Sets, Theoretical Aspects of Reasoning about Data

  • Z. Pawlak
  • Kluwer Academic Publishers, Dordrecht,
  • 1991
2 Excerpts

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