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» Novel Algorithms for Privacy Preserving Utility Mining
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KDD
2007
ACM
276views Data Mining» more  KDD 2007»
14 years 7 months ago
Nonlinear adaptive distance metric learning for clustering
A good distance metric is crucial for many data mining tasks. To learn a metric in the unsupervised setting, most metric learning algorithms project observed data to a lowdimensio...
Jianhui Chen, Zheng Zhao, Jieping Ye, Huan Liu
ACSAC
2005
IEEE
14 years 29 days ago
A Host-Based Approach to Network Attack Chaining Analysis
The typical means by which an attacker breaks into a network is through a chain of exploits, where each exploit in the chain lays the groundwork for subsequent exploits. Such a ch...
Paul Ammann, Joseph Pamula, Julie A. Street, Ronal...
PAISI
2009
Springer
14 years 1 months ago
Discovering Compatible Top-K Theme Patterns from Text Based on Users' Preferences
Discovering a representative set of theme patterns from a large amount of text for interpreting their meaning has always been concerned by researches of both data mining and inform...
Yongxin Tong, Shilong Ma, Dan Yu, Yuanyuan Zhang, ...
ICCS
2007
Springer
14 years 1 months ago
Securely Deliver Data by Multi-path Routing Scheme in Wireless Mesh Networks
Wireless Mesh Networks with static Transit Access Points (TAPs) have many advantages to connect different kinds of networks. While Mobile Ad hoc Networks still have many challenges...
Cao Trong Hieu, Choong Seon Hong
ICDE
2008
IEEE
219views Database» more  ICDE 2008»
14 years 8 months ago
Never Walk Alone: Uncertainty for Anonymity in Moving Objects Databases
Preserving individual privacy when publishing data is a problem that is receiving increasing attention. According to the k-anonymity principle, each release of data must be such th...
Osman Abul, Francesco Bonchi, Mirco Nanni