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A rule measure to represent the temporal changes of data mining patterns
1999 (English)In: Proceedings of the Workshop on Computer Science and Information Technologies CSIT '99, Moscow: University of MEPhl Publishing , 1999Conference paper, Published paper (Refereed)
Abstract [en]

Data mining is the automated extraction of hitherto unknown patterns in large databases. Patterns or rules extracted by mining algorithms are generally true for the current state of the database. As the database state changes due to new transactions these rules may either become invalid or may have increased support. In this paper we present a new rule measure - Rule Trend Analysis (RTA) - which quantifies and represents the trend or behaviour of patterns extracted by data mining systems as these rules evolve along a continuous time interval. This measure is derived using the database log file by analysing transactions that are compliant with the rule and those that are not. We present both the theoretical aspects as well as the results obtained by implementing this technique of data mining rule analysis.

Place, publisher, year, edition, pages
Moscow: University of MEPhl Publishing , 1999.
Identifiers
URN: urn:nbn:se:ltu:diva-31941Local ID: 644156f0-dc8f-11dc-947d-000ea68e967bISBN: 5726202635 (print)OAI: oai:DiVA.org:ltu-31941DiVA, id: diva2:1005175
Conference
International Workshop on Computer Science and Information Technologies : 18/01/1999 - 22/01/1999
Note
Uppr├Ąttat; 1999; 20080216 (cira)Available from: 2016-09-30 Created: 2016-09-30 Last updated: 2018-06-11Bibliographically approved

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Zaslavsky, Arkady

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf