Demchuk, Kostiantyn
(2014)
A Fast Minimal Infrequent Itemset Mining Algorithm.
Masters thesis, National University of Ireland Maynooth.
Abstract
A novel fast algorithm for finding quasi identifiers in large datasets is presented.
Performance measurements on a broad range of datasets demonstrate substantial
reductions in run-time relative to the state of the art and the scalability of the
algorithm to realistically-sized datasets up to several million records.
| Item Type: |
Thesis
(Masters)
|
| Keywords: |
itemset mining; breadth-first algorithm; frequency-based analysis; k-anonymity; performance; load balancing; |
| Academic Unit: |
Faculty of Science and Engineering > Research Institutes > Hamilton Institute |
| Item ID: |
6325 |
| Depositing User: |
IR eTheses
|
| Date Deposited: |
04 Sep 2015 09:54 |
| Funders: |
Science Foundation Ireland under Grant No. 11/PI/1177 |
| URI: |
|
| Use Licence: |
This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available
here |
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