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» Mining Frequent Patterns without Candidate Generation
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ICDE
2008
IEEE
154views Database» more  ICDE 2008»
14 years 9 months ago
Butterfly: Protecting Output Privacy in Stream Mining
Abstract-- Privacy preservation in data mining demands protecting both input and output privacy. The former refers to sanitizing the raw data itself before performing mining. The l...
Ting Wang, Ling Liu
CVPR
2007
IEEE
14 years 10 months ago
Discovery of Collocation Patterns: from Visual Words to Visual Phrases
A visual word lexicon can be constructed by clustering primitive visual features, and a visual object can be described by a set of visual words. Such a "bag-of-words" re...
Junsong Yuan, Ying Wu, Ming Yang
KDD
2009
ACM
239views Data Mining» more  KDD 2009»
14 years 8 months ago
Tell me something I don't know: randomization strategies for iterative data mining
There is a wide variety of data mining methods available, and it is generally useful in exploratory data analysis to use many different methods for the same dataset. This, however...
Heikki Mannila, Kai Puolamäki, Markus Ojala, ...
EMS
2008
IEEE
14 years 2 months ago
A Weighted Utility Framework for Mining Association Rules
Association rule mining (ARM) identifies frequent itemsets from databases and generates association rules by assuming that all items have the same significance and frequency of oc...
M. Sulaiman Khan, Maybin K. Muyeba, Frans Coenen
FGR
2011
IEEE
213views Biometrics» more  FGR 2011»
12 years 11 months ago
Visualisation and prediction of conversation interest through mined social signals
— This paper introduces a novel approach to social behaviour recognition governed by the exchange of non-verbal cues between people. We conduct experiments to try and deduce dist...
Dumebi Okwechime, Eng-Jon Ong, Andrew Gilbert, Ric...