Title :
Research of Mining Algorithm Based on 1NF Strongly Correlated Item Pair
Author_Institution :
Sch. of Comput. Sci. & Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China
Abstract :
In order to reduce the computation cost of candidate pairs, we have developed the Taper algorithm according to 1NF property. The developed TaperR algorithm can cut the number of candidate pairs to improve efficiency. Experimental results exhibit that the new algorithm is well-worked in the mining of all-strong-pairs. So it is more suitable for real relation database system.
Keywords :
data mining; relational databases; TaperR algorithm; all-strong-pairs; candidate pairs; mining algorithm; relation database system; strongly correlated item pair; Algorithm design and analysis; Association rules; Correlation; Relational databases; Upper bound; Association Rules; Data Mining; Multidimensional Structured Database; Top-K Strongly Correlated Item Pair;
Conference_Titel :
Future Computer Science and Education (ICFCSE), 2011 International Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-1-4577-1562-4
DOI :
10.1109/ICFCSE.2011.135
