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Distributed privacy preserving data mining tools are critical for mining multiple databases with a minimum information disclosure. We present a framework including a general model as well as multi-round algorithms for mining horizontally partitioned databases using a privacy preserving k Nearest Neighbor (kNN) classifier.doi:10.1145/1183614.1183757 dblp:conf/cikm/XiongCL06 fatcat:qws3gub7gfgthobwql67xud444