Name
Title | ||
|---|---|---|
Automated support specification for efficient mining of interesting association rules |
Abstract | ||
|---|---|---|
In recent years, the weakness of the canonical support-confidence framework for associations mining has been widely studied. One of the difficulties in applying association rules mining is the setting of support constraints. A high-support constraint avoids the combinatorial explosion in discovering frequent itemsets, but at the expense of missing interesting patterns of low support. Instead of seeking a way to set the appropriate support constraints, all current approaches leave the users in charge of the support setting, which, however, puts the users in a dilemma. This paper is an effort to answer this long-standing open question. According to the notion of confidence and lift measures, we propose an automatic support specification for efficiently mining high-confidence and positive-lift associations without consulting the users. Experimental results show that the proposed method is not only good at discovering high-confidence and positive-lift associations, but also effective in reducing spurious frequent itemsets. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1177/0165551506064364 | J. Information Science |
Keywords | DocType | Volume |
Automated support specification,support constraint,frequent itemsets,efficient mining,low support,positive-lift association,appropriate support constraint,support setting,automatic support specification,association rules mining,associations mining,spurious frequent itemsets,interesting association rule | Journal | 32 |
Issue | ISSN | Citations |
3 | 0165-5515 | 8 |
PageRank | References | Authors |
0.51 | 12 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wen-Yang Lin | 1 | 399 | 35.72 |
| Ming-cheng Tseng | 2 | 73 | 6.47 |