Data mining algorithms analyze and mine databases for discovering implicit, previously unknown and potentially useful knowledge. Frequent pattern mining algorithms discover sets of database items that often occur together. Many of the frequent pattern mining algorithms represent the discovered knowledge in the form of a long textual list containing these sets of frequently co-occurring database items. As the amount of discovered knowledge can be large, it may not be easy for most users to examine and understand such a long textual list of knowledge. In my M.Sc. thesis, I represent both the original database and the discovered knowledge in pictorial form. Specifically, I design a new interactive visualization system for viewing the original transaction data (which are then fed into the frequent pattern mining engine) and for revealing the interesting knowledge discovered from the transaction data in the form of mined patterns.
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:MWU.1993/18326 |
| Date | 03 April 2013 |
| Creators | Carmichael, Christopher Lee |
| Contributors | Leung, Carson K. (Computer Science), Irani, Pourang P. (Computer Science) Wang, Xikui (Statistics) |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Detected Language | English |
Page generated in 0.0154 seconds