Name
Abstract | ||
|---|---|---|
•It is proposed that the missing value in a record is handled by utilising the values of the corresponding fields in the k-NNs of this record.•The proposed method for dealing with missing values allows the use of the traditional blocking techniques to handle the scalability issue.•The existing Bloom filter protocol has been adapted to address both issues of missing values and privacy preservation. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1016/j.is.2017.07.001 | Information Systems |
Keywords | Field | DocType |
Record linkage,Probabilistic record linkage,Privacy preserving record linkage,Missing values,k-Nearest Neighbours,Data encryption | Data mining,Record linkage,Bloom filter,Similarity measure,Confidentiality,Computer science,Missing data,Imputation (statistics) | Journal |
Volume | ISSN | Citations |
71 | 0306-4379 | 2 |
PageRank | References | Authors |
0.37 | 25 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuan Chi | 1 | 2 | 0.37 |
| Jun Hong | 2 | 5 | 1.44 |
| Anna Jurek | 3 | 46 | 6.41 |
| Weiru Liu | 4 | 1597 | 112.05 |
| Dermot O'Reilly | 5 | 2 | 0.37 |