Cited By
View all- van den Braak SBargh MChoenni S(2014)Fraud Indicators Applied to Legal Entities: An Empirical Ranking ApproachDatabase and Expert Systems Applications10.1007/978-3-319-10085-2_9(106-115)Online publication date: 2014
Sharing confidential data for algorithm development by multiple imputation
Article No.: 42, Pages 1 - 4
Abstract
The availability of real-life data sets is of crucial importance for algorithm and application development, as these often require insight into the specific properties of the data. Often, however, such data are not released because of their proprietary and confidential nature. We propose to solve this problem using the statistical technique of multiple imputation, which is used as a powerful method for generating realistic synthetic data sets. Additionally, it is shown how the generated records can be combined into networked data using clustering techniques.
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Published In
July 2013
401 pages
ISBN:9781450319218
DOI:10.1145/2484838
Copyright © 2013 ACM.
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 29 July 2013
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SSDBM '13
SSDBM '13: Conference on Scientific and Statistical Database Management
July 29 - 31, 2013
Maryland, Baltimore, USA
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Cited By
View all- van den Braak SBargh MChoenni S(2014)Fraud Indicators Applied to Legal Entities: An Empirical Ranking ApproachDatabase and Expert Systems Applications10.1007/978-3-319-10085-2_9(106-115)Online publication date: 2014
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