Profiling television viewing using data mining

dc.contributor.author	Chanza, Martin Mudongo
dc.date.accessioned	2013-04-25T12:22:06Z
dc.date.available	2013-04-25T12:22:06Z
dc.date.issued	2013-04-25
dc.description	A dissertation submitted to the Faculty of Science, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Master of Science Johannesburg, February 2013	en_ZA
dc.description.abstract	This study conducted a critical review of data-mining techniques used to extract meaningful information from very large databases. The study aimed to determine cluster analysis methods suitable for the analysis of binary television-viewing data. Television-viewing data from the South African Broadcasting Corporation was used for the analysis. Partitioning and hierarchical clustering methods are compared in the dissertation. The study also examines distance measures used in the clustering of binary data. Particular consideration was given to methods for determining the most appropriate number of clusters to extract. Based on the results of the cluster analysis, four television-viewer profiles were determined. These viewer profiles will enable the South African Broadcasting Corporation to provide viewer-targeted programming.	en_ZA
dc.identifier.uri	http://hdl.handle.net/10539/12688
dc.language.iso	en	en_ZA
dc.subject.lcsh	Data mining.
dc.subject.lcsh	Television viewers - South Africa.
dc.title	Profiling television viewing using data mining	en_ZA
dc.type	Thesis	en_ZA

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