Title :
A dynamic improved apriori algorithm and its experiments in web log mining
Author :
Luan, RuPeng ; Sun, SuFen ; Zhang, JunFeng ; Yu, Feng ; Zhang, Qian
Author_Institution :
Inst. of Agric. Scientech Inf., Beijing Acad. of Agric. & Forestry Sci., Beijing, China
Abstract :
Apriori algorithm is an influential data mining algorithm which can mining the frequent sets of Boolean association rules. But its efficiency is not high and cannot do dynamic mining, for these reasons a new association rules algorithm which is suitable for dynamic database mining was proposed. Furthermore, the new algorithm is applied to the web log mining. Compared with original algorithm, experiments show that the performance of the new algorithm is improved to some extent.
Keywords :
Web sites; data mining; Boolean association rule; Web log mining; data mining algorithm; dynamic database mining; dynamic improved apriori algorithm; Algorithm design and analysis; Association rules; Heuristic algorithms; Itemsets; Software algorithms; Apriori algorithm; correlation analysis; web log mining;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2012 9th International Conference on
Conference_Location :
Sichuan
Print_ISBN :
978-1-4673-0025-4
DOI :
10.1109/FSKD.2012.6234032