Name
Title | ||
|---|---|---|
Privacy-preserving in association rule mining using an improved discrete binary artificial bee colony |
Abstract | ||
|---|---|---|
•A new algorithm is developed for hiding sensitive rules using a binary ABC approach.•We improve the binary ABC to optimize the exploitation for rule hiding.•We apply the improved swarm algorithm for selecting sensitive transactions.•Various experiments are carried out to verify the performance of our algorithms. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.eswa.2019.113097 | Expert Systems with Applications |
Keywords | Field | DocType |
Data mining,Privacy preserving in data mining,Association rule mining,Association rule hiding,Artificial bee colony | Convergence (routing),Data mining,Heuristic,Computer science,Local optimum,Global optimum,Facility location problem,Association rule learning,Knapsack problem,Binary number | Journal |
Volume | ISSN | Citations |
144 | 0957-4174 | 2 |
PageRank | References | Authors |
0.35 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Akbar Telikani | 1 | 21 | 2.70 |
| Amir Hossein Gandomi | 2 | 1836 | 110.25 |
| Asadollah Shahbahrami | 3 | 153 | 19.97 |
| Mohammad Naderi Dehkordi | 4 | 14 | 3.24 |