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dc.contributor.authorAhmed, Naveed
dc.date.accessioned2014-03-04T18:58:24Z
dc.date.available2014-03-04T18:58:24Z
dc.date.issued2010-12
dc.identifier.otherahmed_naveed_201012_ms
dc.identifier.urihttp://purl.galileo.usg.edu/uga_etd/ahmed_naveed_201012_ms
dc.identifier.urihttp://hdl.handle.net/10724/26842
dc.description.abstractThe World Wide Web has become a major source of information dissemination for academia, business and government organizations. Hence, the usability and effectiveness of these websites is increasingly important. User behavior modeling is an important element of such evaluations. We have developed a tool, WebAnalyzer, that lets website administrators select the “best” parameters (number of clusters, distance measures) for clustering user sessions, representations of user behavior while interacting with a web site. Clustering of labeled session data is performed, and both running times and cluster quality measures such as sensitivity and specificity are reported. Website administrators can then select the parameters that achieve the most desirable combination of clustering quality and running time for the labeled data, and apply these parameters to similar but unlabeled datasets to form high-quality user models that permit improved evaluation of website effectiveness.
dc.languageeng
dc.publisheruga
dc.rightspublic
dc.subjectweb site effectiveness
dc.subjectweb usage mining
dc.subjectuser profiling using web logs
dc.titleWebanalyzer
dc.title.alternativea tool for effective Web user behavior modeling
dc.typeThesis
dc.description.degreeMS
dc.description.departmentComputer Science
dc.description.majorComputer Science
dc.description.advisorEileen Kraemer
dc.description.committeeEileen Kraemer
dc.description.committeeKhaled Rasheed
dc.description.committeeJohn A. Miller


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