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Representations of data for repetitive user behaviors using Markov Chains
University of Skövde, School of Informatics.
2020 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

This report presents problematic issues with analyzing user behaviors of a repetitive nature for Anomaly Detection using the Markov Chain model. The users in the data tend to use certain events in succession for a long period of time. Doing the same thing in succession can be normal but when can these users be considered to have an abnormal behavior? The work done in this report presents two alterative ways of representing the data for letting the Markov Chain capture large sections of repeating events without needing to increase the order of the Markov Chain. The presented representations show promising results for an increase in the Markov Chain capability to distinguish users of repetitive nature from each other, as well as suggestions for future development.

Place, publisher, year, edition, pages
2020. , p. 24
National Category
Information Systems, Social aspects
Identifiers
URN: urn:nbn:se:his:diva-18653OAI: oai:DiVA.org:his-18653DiVA, id: diva2:1448007
External cooperation
Insert Coin AB
Subject / course
Informationsteknologi
Educational program
Data Science - Master’s Programme
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Available from: 2020-06-26 Created: 2020-06-26 Last updated: 2020-06-26Bibliographically approved

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CiteExportLink to record
Permanent link

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Citation style
  • apa
  • apa-cv
  • 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