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KDD
2005
ACM
160views Data Mining» more  KDD 2005»
14 years 9 months ago
Optimizing time series discretization for knowledge discovery
Knowledge Discovery in time series usually requires symbolic time series. Many discretization methods that convert numeric time series to symbolic time series ignore the temporal ...
Alfred Ultsch, Fabian Mörchen
KDD
2006
ACM
163views Data Mining» more  KDD 2006»
14 years 9 months ago
New EM derived from Kullback-Leibler divergence
We introduce a new EM framework in which it is possible not only to optimize the model parameters but also the number of model components. A key feature of our approach is that we...
Longin Jan Latecki, Marc Sobel, Rolf Lakämper
KDD
1999
ACM
99views Data Mining» more  KDD 1999»
14 years 1 months ago
On the Merits of Building Categorization Systems by Supervised Clustering
This paper investigates the use of supervised clustering in order to create sets of categories for classi cation of documents. We use information from a pre-existing taxonomy in o...
Charu C. Aggarwal, Stephen C. Gates, Philip S. Yu
KDD
2002
ACM
179views Data Mining» more  KDD 2002»
14 years 9 months ago
From Data To Insight: The Community Of Multimedia Agents
Multimedia Data Mining requires the ability to automatically analyze and understand the content. The Community of Multimedia Agents project (COMMA) is devoted to creating an open ...
Gang Wei, Valery A. Petrushin, Anatole Gershman
KDD
2002
ACM
115views Data Mining» more  KDD 2002»
14 years 9 months ago
Collaborative crawling: mining user experiences for topical resource discovery
The rapid growth of the world wide web had made the problem of topic speci c resource discovery an important one in recent years. In this problem, it is desired to nd web pages wh...
Charu C. Aggarwal