Activity monitoring: noticing interesting changes in behavior
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Postprocessing in machine learning and data mining
ACM SIGKDD Explorations Newsletter - Special issue on “Scalable data mining algorithms”
Pre- and Post-processing in Machine Learning and Data Mining
Machine Learning and Its Applications, Advanced Lectures
Eureka!: A Tool for Interactive Knowledge Discovery
DEXA '02 Proceedings of the 13th International Conference on Database and Expert Systems Applications
Case studies: Commercial domain, single mining tasks systems: visual insights
Handbook of data mining and knowledge discovery
Constructing virtual environments for visual explorers
Virtual space
LISA '02 Proceedings of the 16th USENIX conference on System administration
Online decoding of Markov models under latency constraints
ICML '06 Proceedings of the 23rd international conference on Machine learning
Spectral clustering in telephone call graphs
Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis
Visual Data Mining: An Introduction and Overview
Visual Data Mining
A Visual Data Mining Environment
Visual Data Mining
Spectral Clustering in Social Networks
Advances in Web Mining and Web Usage Analysis
ACM Computing Surveys (CSUR)
Visualizing "typical" and "exotic" Internet traffic data
Computational Statistics & Data Analysis
Testing the fraud detection ability of different user profiles by means of FF-NN classifiers
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part II
Hi-index | 0.01 |
Human pattern recognition skills are remarkable and in manysituations far exceed the ability of automated mining algorithms. Bybuilding domain-specific interfaces that present informationvisually, we can combine human detection with machines‘ far greatercomputational capacity. We illustrate our ideas by describing asuite of visual interfaces we built for telephone fraud detection.