Title :
Algorithms of association rules extraction: State of the art
Author :
Hamida, Amdouni ; Mohsen, Gammoudi Mohamed
Author_Institution :
RIADI Lab., FST, Tunisia
Abstract :
More than a decade, the task of generating associative rules has received considerable attention by researchers because the great need of enterprise deciders to be assisted by systems taking into account unknown knowledge extracted from a huge volume of data. In this paper, we present a survey of the most known algorithms used for associative rules extraction. We give a comparative study between them and we show that they could be classified into some categories.
Keywords :
data mining; association rules extraction algorithms; data mining; enterprise deciders; knowledge extraction; Context; Associatives rules; Closed Itemsets; FCA; Frequent Itemsets; Itemsets;
Conference_Titel :
Communication Software and Networks (ICCSN), 2011 IEEE 3rd International Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-1-61284-485-5
DOI :
10.1109/ICCSN.2011.6014282
