Uncertainty in sequential pattern mining

Muhammad Muzammal*, Rajeev Raman

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)

Abstract

We study uncertainty models in sequential pattern mining. We discuss some kinds of uncertainties that could exist in data, and show how these uncertainties can be modelled using probabilistic databases. We then obtain possible world semantics for them and show how frequent sequences could be mined using the probabilistic frequentness measure.

Original languageEnglish
Title of host publicationData Security and Security Data - 27th British National Conference on Databases, BNCOD 27, Revised Selected Papers
Pages147-150
Number of pages4
DOIs
Publication statusPublished - 2012
Externally publishedYes
Event27th British National Conference on Databases: Data Security and Security Data, BNCOD 27 - Dundee, United Kingdom
Duration: 29 Jun 20101 Jul 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6121 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference27th British National Conference on Databases: Data Security and Security Data, BNCOD 27
Country/TerritoryUnited Kingdom
CityDundee
Period29/06/101/07/10

Keywords

  • Mining Uncertain Data
  • Probabilistic Databases
  • Sequential Pattern Mining
  • Theoretical Foundations of Data Mining

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