A Secure Association Rules Mining Scheme Based on Frequent-Pattern Tree

摘要

Many government organizations and companies want to share their documents in a similar theme to get the joint benefits. Textual document clustering is a powerful data mining technique to analyze the large amount of documents and structure large sets of text or hypertext documents. While doing the document clustering in the distributed environment, it may involve the users' privacy of their own document. In this paper, we propose a framework to do the privacy-preserving text mining among the users under the distributed environment: multiple parties, each having their private documents, want to collaboratively execute agglomerative document clustering without disclosing their private contents to any other parties.