| Autor: |
Li-ping DING, Guo-qing LU |
| Jazyk: |
čínština |
| Rok vydání: |
2014 |
| Předmět: |
|
| Zdroj: |
Tongxin xuebao, Vol 35, Pp 200-209 (2014) |
| Druh dokumentu: |
article |
| ISSN: |
1000-436X |
| DOI: |
10.3969/j.issn.1000-436x.2014.10.023 |
| Popis: |
Frequent pattern mining is an exploratory problem in the field of data mining.However,directly releasing the discovered frequent patterns and the corresponding true supports may reveal the individuals’ privacy.The state-of-the-art solution for this problem is differential privacy,which offers a strong degree of privacy protection by adding noise.Firstly,the theoretical basis of differential privacy was introduced.Then,three representative frequent pattern mining methods under differential privacy were summarized and compared in detail.Finally,some future research directions were discussed. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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