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Text Classification of Legitimate and Rogue online Privacy Policies: Manual Analysis and a Machine Learning Experimental Approach
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering. (Computer Science)
2016 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Place, publisher, year, edition, pages
2016. , p. 59
Keywords [en]
Privacy policy, legitimate, rogue, text-classification, training, testing, learning algorithms
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:bth-13363OAI: oai:DiVA.org:bth-13363DiVA, id: diva2:1045553
Subject / course
DV2566 Master's Thesis (120 credits) in Computer Science
Educational program
DVACS Master of Science Programme in Computer Science
Presentation
2016-09-28, J1630, BTH, Karlskrona, 03:00 (English)
Supervisors
Available from: 2016-11-22 Created: 2016-11-10 Last updated: 2018-01-13Bibliographically approved

Open Access in DiVA

fulltext(704 kB)185 downloads
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File name FULLTEXT02.pdfFile size 704 kBChecksum SHA-512
dded62f454d08ff07e0b1d9077cdbb62336c5cbd254ea5de02b462ee42624c96b369e39dbc00b5236d80972880ace47b8e5eb292b2a5cd678f4c0fdaa858979a
Type fulltextMimetype application/pdf

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Rekanar, Kaavya
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CiteExportLink to record
Permanent link

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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
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