Knowledge Discovery from Data (TKDD)


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ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 2 Issue 3, October 2008

Incremental tensor analysis: Theory and applications
Jimeng Sun, Dacheng Tao, Spiros Papadimitriou, Philip S. Yu, Christos Faloutsos
Article No.: 11
DOI: 10.1145/1409620.1409621

How do we find patterns in author-keyword associations, evolving over time? Or in data cubes (tensors), with product-branchcustomer sales information? And more generally, how to summarize high-order data cubes (tensors)? How to...

Privacy-preserving classification of vertically partitioned data via random kernels
Olvi L. Mangasarian, Edward W. Wild, Glenn M. Fung
Article No.: 12
DOI: 10.1145/1409620.1409622

We propose a novel privacy-preserving support vector machine (SVM) classifier for a data matrix A whose input feature columns are divided into groups belonging to different entities. Each entity is unwilling to share its group of columns or...

On disclosure risk analysis of anonymized itemsets in the presence of prior knowledge
LAKS V. S. Lakshmanan, Raymond T. Ng, Ganesh Ramesh
Article No.: 13
DOI: 10.1145/1409620.1409623

Decision makers of companies often face the dilemma of whether to release data for knowledge discovery, vis-a-vis the risk of disclosing proprietary or sensitive information. Among the various methods employed for “sanitizing” the data...

Privacy-preserving decision trees over vertically partitioned data
Jaideep Vaidya, Chris Clifton, Murat Kantarcioglu, A. Scott Patterson
Article No.: 14
DOI: 10.1145/1409620.1409624

Privacy and security concerns can prevent sharing of data, derailing data-mining projects. Distributed knowledge discovery, if done correctly, can alleviate this problem. We introduce a generalized privacy-preserving variant of the ID3 algorithm...