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» Describing Semistructured Data
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KDD
1998
ACM
107views Data Mining» more  KDD 1998»
15 years 11 months ago
Giga-Mining
Wedescribe an industrial-strength data mining application in telecommunications.Theapplication requires building a short (7 byte) profile for all telephonenumbersseen on a large t...
Corinna Cortes, Daryl Pregibon
KDD
1997
ACM
120views Data Mining» more  KDD 1997»
15 years 11 months ago
Discovering Trends in Text Databases
We describe a system we developed for identifying trends in text documents collected over a period of time. Trends can be used, for example, to discover that a company is shifting...
Brian Lent, Rakesh Agrawal, Ramakrishnan Srikant
KDD
1997
ACM
109views Data Mining» more  KDD 1997»
15 years 11 months ago
Beyond Concise and Colorful: Learning Intelligible Rules
A variety of techniques from statistics, signal processing, pattern recognition, machine learning, and neural networks have been proposed to understand data by discovering useful ...
Michael J. Pazzani, Subramani Mani, William Rodman...
FOCS
1992
IEEE
15 years 11 months ago
Dynamic Half-Space Reporting, Geometric Optimization, and Minimum Spanning Trees
We describe dynamic data structures for half-space range reporting and for maintaining the minima of a decomposable function. Using these data structures, we obtain efficient dyna...
Pankaj K. Agarwal, David Eppstein, Jirí Mat...
182
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APVIS
2010
15 years 8 months ago
GMap: Visualizing graphs and clusters as maps
Information visualization is essential in making sense out of large data sets. Often, high-dimensional data are visualized as a collection of points in 2-dimensional space through...
Emden R. Gansner, Yifan Hu, Stephen G. Kobourov