An Approach to Outsourcing Data Mining Tasks While Protecting Business Intelligence and Customer Privacy
Data mining is playing an important role in decision making. It is beneficial to outsource data mining tasks if an organization does not have required expertise in-house. However, the organization may lose business intelligence and customer privacy during this outsourcing process. In this paper, we...
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| Main Authors: | , , |
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| Format: | text |
| Language: | English |
| Published: |
Institutional Knowledge at Singapore Management University
2006
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| Subjects: | |
| Online Access: | https://ink.library.smu.edu.sg/sis_research/610 http://dx.doi.org/10.1109/ICDMW.2006.26 |
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| Institution: | Singapore Management University |
| Language: | English |
| Summary: | Data mining is playing an important role in decision making. It is beneficial to outsource data mining tasks if an organization does not have required expertise in-house. However, the organization may lose business intelligence and customer privacy during this outsourcing process. In this paper, we present a Bloom filter based solution to enable organizations to outsource their tasks of mining association rules while protecting their business intelligence and customer privacy. Our approach can achieve high precision in data mining by trading-off storage requirements. |
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