document: Privacy-preserving k-means clustering over vertically partitioned data Privacy and security concerns can prevent sharing of data , derailing data mining projects . Distributed knowledge discovery , if done correctly , can alleviate this problem . The key is to obtain valid results , while providing guarantees on the ( non ) disclosure of data . We present a method for k-means clustering when different sites contain different attributes for a common set of entities . Each site learns the cluster of each entity , but learns nothing about the attributes at other sites .
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