Association rule hiding over data streams

dc.contributorGraduate Program in Computer Engineering.
dc.contributor.advisorGündem, Taflan.
dc.contributor.authorGünay, Ufuk.
dc.date.accessioned2023-03-16T10:06:30Z
dc.date.available2023-03-16T10:06:30Z
dc.date.issued2007.
dc.description.abstractThis study is about an endeavor towards combining association rule mining over data streams and association rule hiding for traditional databases. Mainly, a system for association rule hiding over data streams will be introduced, and related background will be developed in detail. Although there are many algorithms, some of which perform very well, developed for both association rule mining over data streams and association rule hiding for traditional databases so far, we have not meet a work on stream association rule hiding, namely a work which combines these two research areas. In this work, we introduce a new system in which we merge these two interesting research areas of association rule mining. We apply our stream association rule hiding algorithm on synthetic data. We also run our algorithm over a template guided XML data. Our performance tests show that proposed system hides association rules for data streams efficiently.
dc.format.extent30cm.
dc.format.pagesxii, 59 leaves;
dc.identifier.otherCMPE 2007 G87
dc.identifier.urihttps://digitalarchive.library.bogazici.edu.tr/handle/123456789/12513
dc.publisherThesis (M.S.)-Bogazici University. Institute for Graduate Studies in Science and Engineering, 2007.
dc.relationIncludes appendices.
dc.relationIncludes appendices.
dc.subject.lcshData mining.
dc.subject.lcshComputer algorithms.
dc.titleAssociation rule hiding over data streams

Files

Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
b1459671.001985.001.PDF
Size:
426.75 KB
Format:
Adobe Portable Document Format

Collections