We consider the problem of private efficient data mining of vertically-partitioned databases. Each of several parties holds a column of a data matrix (a vector) and the parties wan...
Yuval Ishai, Tal Malkin, Martin J. Strauss, Rebecc...
We present an ensemble learning approach that achieves accurate predictions from arbitrarily partitioned data. The partitions come from the distributed processing requirements of ...
Larry Shoemaker, Robert E. Banfield, Lawrence O. H...
In this paper we process and analyze web search engine query and click data from the perspective of the documents (URL’s) selected. We initially define possible document categor...
We present an open framework for visual mining of CVS software repositories. We address three aspects: data extraction, analysis and visualization. We first discuss the challenges...
Anomaly detection in IP networks, detection of deviations from what is considered normal, is an important complement to misuse detection based on known attack descriptions. Perfor...