Name
Title | ||
|---|---|---|
The arithmetic of discover Cyclic Association Rules based on difference sequence arithmetic clustering |
Abstract | ||
|---|---|---|
The routine Cyclic Association Rules and its upgrading alternatives were found with some problems as these:Some disadvantage of technique that compartmentalize a cycle into several time segments; The basic arithmetic use Apriori Arithmetic ,Their disadvantage are huge the candidate items and low-level efficiency. In regard to these problems, a new Cyclic Association Rules method was discussed. The new approach addressed these problems by adopting different methods.It chose the time sequence vector consists of the support of item to cluster, and using DB Index to determine the Optimal Class Number of Cluster, accordingly confirm well and truly time segments of cycle. And we introduced Cyclic FP-tree(CFP-tree) to discover Cyclic Association Rules, Cyclic FP-tree based on FP-tree arithmetic,FP-tree arithmetic excelled evidently Apriori arithmetic, CFP-tree handle cycle clipping technology based on conditional FP-tree to improve markedly efficiency of arithmetic. The findings tested Data Set of high-dimensional industrial authenticity. The findings prove the efficiency of the new approach in a broad scale. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/FSKD.2010.5569688 | FSKD |
Keywords | Field | DocType |
database management systems,cyclic association rules,db index,pattern clustering,optimal class number,difference sequence arithmetic,time series vector,cyclic fp-tree,tree data structures,cyclic association rules arithmetic,cyclic fp tree,apriori arithmetic,data mining,difference sequence arithmetic clustering,cycle clipping technology,association rules,indexes,forestry,indexation,time series analysis,agriculture,time series,association rule | Time series,Computer science,Pattern clustering,Class number,Tree (data structure),A priori and a posteriori,Arithmetic,Association rule learning,Cluster analysis | Conference |
Volume | ISBN | Citations |
5 | 978-1-4244-5931-5 | 0 |
PageRank | References | Authors |
0.34 | 5 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bin Zeng | 1 | 0 | 0.34 |
| Chao Luo | 2 | 58 | 17.22 |
| Xiao-Li Jiang | 3 | 0 | 0.34 |
| Sun Jun | 4 | 0 | 0.34 |