Name
Abstract | ||
|---|---|---|
•Running time and memory consumption comparison of 10 HUI mining algorithms.•Comparison tests using 9 real world and 72 synthetic datasets.•d2HUP and EFIM are the top-2 performers regarding running time.•d2HUP is fastest when the data is sparse or the average transaction length is large.•EFIM is the most efficient algorithm regarding memory consumption. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.eswa.2018.02.008 | Expert Systems with Applications |
Keywords | Field | DocType |
Itemset mining,High utility itemsets,State-of-the-art high utility itemset mining | Recommender system,Data mining,Computer science,Algorithm,Artificial intelligence,Database transaction,Stock market prediction,Machine learning,Empirical research | Journal |
Volume | Issue | ISSN |
101 | C | 0957-4174 |
Citations | PageRank | References |
1 | 0.35 | 26 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chongsheng Zhang | 1 | 60 | 3.61 |
| George Almpanidis | 2 | 63 | 5.88 |
| Wanwan Wang | 3 | 1 | 0.35 |
| Changchang Liuc | 4 | 56 | 4.65 |