Discovery of frequent DATALOG patterns View Full Text


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Article Info

DATE

1999-03

AUTHORS

Luc Dehaspe, Hannu Toivonen

ABSTRACT

Discovery of frequent patterns has been studied in a variety of data mining settings. In its simplest form, known from association rule mining, the task is to discover all frequent itemsets, i.e., all combinations of items that are found in a sufficient number of examples. The fundamental task of association rule and frequent set discovery has been extended in various directions, allowing more useful patterns to be discovered with special purpose algorithms. We present WARMR, a general purpose inductive logic programming algorithm that addresses frequent query discovery: a very general DATALOG formulation of the frequent pattern discovery problem. The motivation for this novel approach is twofold. First, exploratory data mining is well supported: WARMR offers the flexibility required to experiment with standard and in particular novel settings not supported by special purpose algorithms. Also, application prototypes based on WARMR can be used as benchmarks in the comparison and evaluation of new special purpose algorithms. Second, the unified representation gives insight to the blurred picture of the frequent pattern discovery domain. Within the DATALOG formulation a number of dimensions appear that relink diverged settings. We demonstrate the frequent query approach and its use on two applications, one in alarm analysis, and one in a chemical toxicology domain. More... »

PAGES

7-36

References to SciGraph publications

  • 1997-09. Levelwise Search and Borders of Theories in Knowledge Discovery in DATA MINING AND KNOWLEDGE DISCOVERY
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  • 1998. Relational reinforcement learning in INDUCTIVE LOGIC PROGRAMMING
  • 1999. A declarative language bias for levelwise search of first-order regularities in FOUNDATIONS OF INTELLIGENT SYSTEMS
  • 1997. Discovery of first-order regularities in a relational database using ofine candidate determination in INDUCTIVE LOGIC PROGRAMMING
  • 1997. Carcinogenesis predictions using ILP in INDUCTIVE LOGIC PROGRAMMING
  • 1997-09. Discovery of Frequent Episodes in Event Sequences in DATA MINING AND KNOWLEDGE DISCOVERY
  • 1986-03. Induction of decision trees in MACHINE LEARNING
  • 1999-12. Rule Discovery in Telecommunication Alarm Data in JOURNAL OF NETWORK AND SYSTEMS MANAGEMENT
  • 1997. An algorithm for multi-relational discovery of subgroups in PRINCIPLES OF DATA MINING AND KNOWLEDGE DISCOVERY
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1023/a:1009863704807

    DOI

    http://dx.doi.org/10.1023/a:1009863704807

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1011882918


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