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KDD
2007
ACM
165views Data Mining» more  KDD 2007»
16 years 1 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...
KDD
2007
ACM
152views Data Mining» more  KDD 2007»
16 years 1 months ago
A framework for classification and segmentation of massive audio data streams
In recent years, the proliferation of VOIP data has created a number of applications in which it is desirable to perform quick online classification and recognition of massive voi...
Charu C. Aggarwal
KDD
2006
ACM
272views Data Mining» more  KDD 2006»
16 years 1 months ago
YALE: rapid prototyping for complex data mining tasks
KDD is a complex and demanding task. While a large number of methods has been established for numerous problems, many challenges remain to be solved. New tasks emerge requiring th...
Ingo Mierswa, Michael Wurst, Ralf Klinkenberg, Mar...
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KDD
2004
ACM
124views Data Mining» more  KDD 2004»
16 years 1 months ago
Support envelopes: a technique for exploring the structure of association patterns
This paper introduces support envelopes--a new tool for analyzing association patterns--and illustrates some of their properties, applications, and possible extensions. Specifical...
Michael Steinbach, Pang-Ning Tan, Vipin Kumar
KDD
2003
ACM
180views Data Mining» more  KDD 2003»
16 years 1 months ago
Classifying large data sets using SVMs with hierarchical clusters
Support vector machines (SVMs) have been promising methods for classification and regression analysis because of their solid mathematical foundations which convey several salient ...
Hwanjo Yu, Jiong Yang, Jiawei Han