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170
Voted
VIS
2009
IEEE
399views Visualization» more  VIS 2009»
16 years 4 months ago
Visual Human+Machine Learning
In this paper we describe a novel method to integrate interactive visual analysis and machine learning to support the insight generation of the user. The suggested approach combine...
Raphael Fuchs, Jürgen Waser, Meister Eduard GrÃ...
141
Voted
KDD
2007
ACM
170views Data Mining» more  KDD 2007»
16 years 4 months ago
From frequent itemsets to semantically meaningful visual patterns
Data mining techniques that are successful in transaction and text data may not be simply applied to image data that contain high-dimensional features and have spatial structures....
Junsong Yuan, Ying Wu, Ming Yang
141
Voted
KDD
2004
ACM
210views Data Mining» more  KDD 2004»
16 years 4 months ago
Visually mining and monitoring massive time series
Moments before the launch of every space vehicle, engineering discipline specialists must make a critical go/no-go decision. The cost of a false positive, allowing a launch in spi...
Jessica Lin, Eamonn J. Keogh, Stefano Lonardi, Jef...
301
Voted
SIGMOD
2008
ACM
215views Database» more  SIGMOD 2008»
16 years 3 months ago
CSV: visualizing and mining cohesive subgraphs
Extracting dense sub-components from graphs efficiently is an important objective in a wide range of application domains ranging from social network analysis to biological network...
Nan Wang, Srinivasan Parthasarathy, Kian-Lee Tan, ...
135
Voted
VIZSEC
2004
Springer
15 years 9 months ago
Managing attack graph complexity through visual hierarchical aggregation
We describe a framework for managing network attack graph complexity through interactive visualization, which includes hierarchical aggregation of graph elements. Aggregation coll...
Steven Noel, Sushil Jajodia