Ak Anonymity Clustering Method for Effective Data Privacy Preservation 1st Edition by Chuang Cheng Chiu, Chieh Yuan Tsai 9783540738701

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ISBN 13: 9783540738701

Author: Chuang Cheng Chiu, Chieh Yuan Tsai

Data privacy preservation has drawn considerable interests in data mining research recently. The k-anonymity model is a simple and practical approach for data privacy preservation. This paper proposes a novel clustering method for conducting the k-anonymity model effectively. In the proposed clustering method, feature weights are automatically adjusted so that the information distortion can be reduced. A set of experiments show that the proposed method keeps the benefit of scalability and computational efficiency when comparing to other popular clustering algorithms.

Ak Anonymity Clustering Method for Effective Data Privacy Preservation 1st Table of contents:

1 Introduction

2 The Proposed k-Anonymity Clustering Method

3 Experiments

4 Conclusion

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