Date of Award
January 2016
Degree Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Computer Science
First Advisor
Mohammad A Hasan
Committee Member 1
Snehasis Mokhopadhyay
Committee Member 2
Chris Clifton
Committee Member 3
Elisa Bertino
Committee Member 4
Jean Honorio
Abstract
The traditional frequent pattern mining algorithms generate an exponentially large number of patterns of which a substantial portion are not much significant for many data analysis endeavours. Due to this, the discovery of a small number of interesting patterns from the exponentially large number of frequent patterns according to a particular user's interest is an important task. Existing works on pattern
Recommended Citation
Bhuiyan, Md Mansurul Alam, "GENERIC FRAMEWORKS FOR INTERACTIVE PERSONALIZED INTERESTING PATTERN DISCOVERY" (2016). Open Access Dissertations. 1378.
https://docs.lib.purdue.edu/open_access_dissertations/1378
