A comparative study on innovative approaches for privacy-preservation in knowledge discovery-Reference-Cited by-同舟云学术

A comparative study on innovative approaches for privacy-preservation in knowledge discovery

Published:2017 Issue: Volume: Page:
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Container-title:Proceedings of the 9th International Conference on Information Management and Engineering - ICIME 2017
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Author:

Amiri Fatemeh¹,Quirchmayr Gerald¹

Affiliation:

1. University of Vienna, Vienna, Austria

Publisher

ACM Press

Reference87 articles.

1. Fayyad, U. M., Piatetsky-Shapiro, G., Smyth, P. and Uthurusamy, R. Advances in knowledge discovery and data mining. AAAI press Menlo Park, 1996.

2. Narwaria, M. and Arya, S. Privacy preserving data mining---'A state of the art'. IEEE, City, 2016.

3. Korba, L. Privacy in distributed electronic commerce. IEEE, City, 2002.

4. Sairam, M. Sowndarya," Performance Analysis of Clustering Algorithms in Detecting Outliers". International Journal of Computer Science and Information Technologies, 2, 1 (2011), 486--488.

5. Chen, H. Intelligence and security informatics: information systems perspective. Decision Support Systems, 41, 3 (2006), 555--559.

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