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» A Partial-Repeatability Approach to Data Mining
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114
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PVLDB
2010
95views more  PVLDB 2010»
15 years 2 months ago
Small Domain Randomization: Same Privacy, More Utility
Random perturbation is a promising technique for privacy preserving data mining. It retains an original sensitive value with a certain probability and replaces it with a random va...
Rhonda Chaytor, Ke Wang
154
Voted
SDM
2003
SIAM
184views Data Mining» more  SDM 2003»
15 years 5 months ago
Finding Clusters of Different Sizes, Shapes, and Densities in Noisy, High Dimensional Data
The problem of finding clusters in data is challenging when clusters are of widely differing sizes, densities and shapes, and when the data contains large amounts of noise and out...
Levent Ertöz, Michael Steinbach, Vipin Kumar
137
Voted
KDD
2000
ACM
133views Data Mining» more  KDD 2000»
15 years 7 months ago
Data selection for support vector machine classifiers
The problem of extracting a minimal number of data points from a large dataset, in order to generate a support vector machine (SVM) classifier, is formulated as a concave minimiza...
Glenn Fung, Olvi L. Mangasarian
131
Voted
JCST
2008
121views more  JCST 2008»
15 years 3 months ago
Clustering Text Data Streams
Abstract Clustering text data streams is an important issue in data mining community and has a number of applications such as news group filtering, text crawling, document organiza...
Yubao Liu, Jiarong Cai, Jian Yin, Ada Wai-Chee Fu
153
Voted
PKDD
2000
Springer
144views Data Mining» more  PKDD 2000»
15 years 7 months ago
Fast Hierarchical Clustering Based on Compressed Data and OPTICS
: One way to scale up clustering algorithms is to squash the data by some intelligent compression technique and cluster only the compressed data records. Such compressed data recor...
Markus M. Breunig, Hans-Peter Kriegel, Jörg S...