Name
Title | ||
|---|---|---|
Probabilistic Frequent Itemsets Mining Based on Expectation Bound over Uncertain Database |
Abstract | ||
|---|---|---|
Frequent itemsets discovery is popular in database communities recently. Because real data is often affected by noise, in this paper, we study to find frequent itemsets over probabilistic database under the Possible World Semantics. It is challenging because there may be exponential number of possible worlds for probabilistic database. Although several efficient algorithms are proposed in the literature, it is hard to mine frequent itemsets in large uncertain database due to the high time consuming. To address this issue, we propose an efficient algorithm to mine probabilistic frequent itemsets. A pruning strategy is also presented to accelerate the process of generating candidates. Extensive experiments have been done on synthetic and real databases, demonstrating that the proposed method preforms better than state-of-art methods in most cases. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/ISPAN-FCST-ISCC.2017.92 | 2017 14th International Symposium on Pervasive Systems, Algorithms and Networks & 2017 11th International Conference on Frontier of Computer Science and Technology & 2017 Third International Symposium of Creative Computing (ISPAN-FCST-ISCC) |
Keywords | Field | DocType |
Uncertain Database,Probabilistic Frequent Patterns,Support expectation bound | Algorithm design,Computer science,Probabilistic logic,Semantics,Database,Probabilistic database,Possible world | Conference |
ISBN | Citations | PageRank |
978-1-5386-0841-8 | 0 | 0.34 |
References | Authors | |
11 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lihai Nie | 1 | 0 | 0.34 |
| Zhi-yang Li | 2 | 146 | 26.37 |
| Heng Qi | 3 | 218 | 30.45 |
| Weijiang Liu | 4 | 0 | 0.34 |
| Wenyu Qu | 5 | 576 | 66.94 |