Document Type
Conference Proceeding
Publication Date
8-2007
Abstract
The service-oriented infrastructure has become popular for collaboratively mining data distributed over organizations [3], where the participants are the data providers who submit their perturbed datasets to the designated data mining service provider (the data miner) for mining commonly interested models.
Repository Citation
Chen, K.,
& Liu, L.
(2007). Space Adaptation: Privacy-Preserving Multiparty Collaborative Mining with Geometric Perturbation. Proceedings of the Twenty-Sixth Annual ACM Symposium on Principles of Distributed Computing, 324-325.
https://corescholar.libraries.wright.edu/knoesis/904
DOI
10.1145/1281100.1281154
Included in
Bioinformatics Commons, Communication Technology and New Media Commons, Databases and Information Systems Commons, OS and Networks Commons, Science and Technology Studies Commons
Comments
Presented at the 26th Annual ACM Symposium on Principles of Distributed Computing, Portland, OR, August 12-15, 2007.