dc.contributor.advisor |
Lingras, Pawan |
|
dc.creator |
Yan, Rui |
|
dc.date.accessioned |
2011-05-09T12:32:26Z |
|
dc.date.available |
2011-05-09T12:32:26Z |
|
dc.date.issued |
2004 |
|
dc.identifier.other |
QA278 Y36 2004 |
|
dc.identifier.uri |
http://library2.smu.ca/xmlui/handle/01/22622 |
|
dc.description |
xviii, 117 leaves : ill. (some col.) ; 28 cm. |
|
dc.description |
Includes abstract. |
|
dc.description |
Includes bibliographical references (leaves 114-117). |
|
dc.description.abstract |
Clustering is an important aspect of data mining. Many data mining applications tend to be more amenable to non-conventional clustering techniques. In this research three clustering methods are employed to analyze the web usage and super market data sets: conventional, rough set and fuzzy methods. Interval clusters based on fuzzy memberships are also created. The web usage data were collected from three educational web sites. The supermarket data spanned twenty-six weeks of transactions from twelve stores spanning three regions. Cluster sizes obtained using the three methods are compared, and cluster characteristics are analyzed. Web users and supermarket customers tend to change their characteristics over a period of time. These changes may be temporary or permanent. This thesis also studies the changes in cluster characteristics over time. Both experiments demonstrate that the rough and fuzzy methods are more subtle and accurate in capturing the slight differences among clusters. |
|
dc.description.provenance |
Made available in DSpace on 2011-05-09T12:32:26Z (GMT). No. of bitstreams: 0 |
en |
dc.language.iso |
en |
|
dc.publisher |
Halifax, N.S. : Saint Mary's University |
|
dc.subject.lcc |
QA278 |
|
dc.subject.lcsh |
Data mining |
|
dc.subject.lcsh |
Cluster analysis |
|
dc.subject.lcsh |
Web usage mining |
|
dc.subject.lcsh |
Internet users |
|
dc.subject.lcsh |
Consumer behavior |
|
dc.title |
Temporal mining of the web and supermarket data using fuzzy and rough set clustering |
|
dc.type |
Text |
|
thesis.degree.name |
Master of Science in Applied Science |
|
thesis.degree.level |
Masters |
|
thesis.degree.discipline |
Mathematics and Computing Science |
|
thesis.degree.grantor |
Saint Mary's University (Halifax, N.S.) |
|