In the recent years, our ability of collecting information rapidly increases and huge databases that change over time in a high frequency have been developed. On the other hand, th...
Data distortion is a critical component to preserve privacy in security-related data mining applications, such as in data miningbased terrorist analysis systems. We propose a spars...
We are proposing a novel method that makes it possible to analyze high dimensional data with arbitrary shaped projected clusters and high noise levels. At the core of our method l...
Amihood Amir, Reuven Kashi, Nathan S. Netanyahu, D...
There has been a renewed interest in understanding the structure of high dimensional data set based on manifold learning. Examples include ISOMAP [25], LLE [20] and Laplacian Eige...
We present a new approach to large-scale graph mining based on so-called backbone refinement classes. The method efficiently mines tree-shaped subgraph descriptors under minimum f...