Name
Abstract | ||
|---|---|---|
Zero-suppressed decision diagrams (ZDDs) are a data structure for representing combinations over item sets. They have been applied to many areas such as data mining. When ZDDs represent large-scale sparse datasets, they tend to obtain an unbalanced form, which results performance degradation. In this paper, we propose a new data structure three-way indexing ZDD, as a variant of ZDDs. We furthermore present algorithms to convert between three-way indexing ZDDs and ordinary ZDDs. Experimental results show the effectiveness of our data structure and algorithms. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/978-3-319-13186-3_41 | Lecture Notes in Artificial Intelligence |
Keywords | Field | DocType |
ZDD,Zero-suppressed binary decision diagram,Ternary search tree,Membership query | Data mining,Data structure,Computer science,Search engine indexing,Artificial intelligence,Ternary search tree,Machine learning | Conference |
Volume | ISSN | Citations |
8643 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 5 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hiroshi Aoki | 1 | 0 | 0.34 |
| Takahisa Toda | 2 | 11 | 3.53 |
| Shin-ichi Minato | 3 | 725 | 84.72 |