Publication
Title
MIME : a framework for interactive visual pattern mining
Author
Abstract
We present a framework for interactive visual pattern mining. Our system enables the user to browse through the data and patterns easily and intuitively, using a toolbox consisting of interestingness measures, mining algorithms and post-processing algorithms to assist in identifying interesting patterns. By mining interactively, we enable the user to combine their subjective interestingness measure and background knowledge with a wide variety of objective measures to easily and quickly mine the most important and interesting patterns. Basically, we enable the user to become an essential part of the mining algorithm. Our demo currently applies to mining interesting itemsets and association rules, and its extension to episodes and decision trees is ongoing.
Language
English
Source (book)
KDD '11 : proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
Publication
New York, N.Y. : ACM , 2011
ISBN
978-1-4503-0813-7
DOI
10.1145/2020408.2020529
Volume/pages
p. 757-760
Full text (Publisher's DOI)
UAntwerpen
Faculty/Department
Research group
Project info
Principles of Pattern Set Mining for structured data.
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Record
Identifier
Creation 23.04.2013
Last edited 07.10.2022
To cite this reference