Cone Trees: animated 3D visualizations of hierarchical information
CHI '91 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Readings in information visualization: using vision to think
Readings in information visualization: using vision to think
RuleViz: a model for visualizing knowledge discovery process
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Information visualization in data mining and knowledge discovery
Information visualization in data mining and knowledge discovery
Methods and Problems in Data Mining
ICDT '97 Proceedings of the 6th International Conference on Database Theory
A visualization tool for interactive learning of large decision trees
ICTAI '00 Proceedings of the 12th IEEE International Conference on Tools with Artificial Intelligence
Mining hepatitis data with temporal abstraction
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Knowledge visualization in hepatitis study
APVis '06 Proceedings of the 2006 Asia-Pacific Symposium on Information Visualisation - Volume 60
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part I
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Viewing knowledge discovery as a user-centered process that requires an effective collaboration between the user and the discovery system, our work aims to support an active role of the user in that process by developing synergistic visualization tools integrated in our discovery system D2MS. These tools provide an ability of visualizing the entire process of knowledge discovery in order to help the user with data preprocessing, selecting mining algorithms and parameters, evaluating and comparing discovered models, and taking control of the whole discover process. Our case-studies with two medical datasets on meningitis and stomach cancer show that, with visualization tools in D2MS, the user gains better insight in each step of the knowledge discovery process as well the relationship between data and discovered knowledge.