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» Providing k-anonymity in data mining
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SDM
2009
SIAM
144views Data Mining» more  SDM 2009»
15 years 7 months ago
On Segment-Based Stream Modeling and Its Applications.
The primary constraint in the effective mining of data streams is the large volume of data which must be processed in real time. In many cases, it is desirable to store a summary...
Charu C. Aggarwal
SIGKDD
2000
139views more  SIGKDD 2000»
14 years 9 months ago
Support Vector Machines: Hype or Hallelujah?
Support Vector Machines (SVMs) and related kernel methods have become increasingly popular tools for data mining tasks such as classification, regression, and novelty detection. T...
Kristin P. Bennett, Colin Campbell
IADIS
2003
14 years 11 months ago
Assessing Web Usage Profiles
Today the World Wide Web is seen as an unique medium for interaction. Every organisation has or is about to have its own Web site, aiming to attract as much visitors as each one c...
Anália Lourenço, Orlando Belo
KDD
2006
ACM
128views Data Mining» more  KDD 2006»
15 years 10 months ago
Workload-aware anonymization
Protecting data privacy is an important problem in microdata distribution. Anonymization algorithms typically aim to protect individual privacy, with minimal impact on the quality...
Kristen LeFevre, David J. DeWitt, Raghu Ramakrishn...
KDD
2003
ACM
155views Data Mining» more  KDD 2003»
15 years 10 months ago
Graph-based anomaly detection
Anomaly detection is an area that has received much attention in recent years. It has a wide variety of applications, including fraud detection and network intrusion detection. A ...
Caleb C. Noble, Diane J. Cook