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» Hierarchical exploration of large multivariate data sets
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KDD
2006
ACM
160views Data Mining» more  KDD 2006»
15 years 10 months ago
Coherent closed quasi-clique discovery from large dense graph databases
Frequent coherent subgraphscan provide valuable knowledgeabout the underlying internal structure of a graph database, and mining frequently occurring coherent subgraphs from large...
Zhiping Zeng, Jianyong Wang, Lizhu Zhou, George Ka...
RSCTC
2010
Springer
142views Fuzzy Logic» more  RSCTC 2010»
14 years 7 months ago
Learning from Imbalanced Data in Presence of Noisy and Borderline Examples
In this paper we studied re-sampling methods for learning classifiers from imbalanced data. We carried out a series of experiments on artificial data sets to explore the impact of ...
Krystyna Napierala, Jerzy Stefanowski, Szymon Wilk
KDD
2007
ACM
165views Data Mining» more  KDD 2007»
15 years 10 months ago
Efficient and effective explanation of change in hierarchical summaries
Dimension attributes in data warehouses are typically hierarchical (e.g., geographic locations in sales data, URLs in Web traffic logs). OLAP tools are used to summarize the measu...
Deepak Agarwal, Dhiman Barman, Dimitrios Gunopulos...

Publication
273views
14 years 4 months ago
 3D Visualization of Multiple Time Series on Maps
Abstract—In the analysis of spatially-referenced timedependent data, gaining an understanding of the spatiotemporal distributions and relationships among the attributes in the...
Sidharth Thakur, Andrew J. Hanson
TVCG
2002
123views more  TVCG 2002»
14 years 9 months ago
Information Visualization and Visual Data Mining
Never before in history data has been generated at such high volumes as it is today. Exploring and analyzing the vast volumes of data becomes increasingly difficult. Information vi...
Daniel A. Keim