ECLAT-Based Association Rules Mining for Education Training Centre

Abstract

Frequent pattern mining has become an important data mining task because finding such frequent patterns play an essential role in mining associations, correlation and many other interesting relationships among data. This paper describes how effectively use the vertical association rule mining approach in finding correlated courses in Human Resource Centre. Although there are many algorithms for vertical approach, ECLAT (Equivalence CLASS Transformation) algorithm, developed by Zaki [6], is used for our system implementation. By using ECLAT method, useful frequent itemsets (courses) are obtained easily by saving the database scanning time. These frequent itemsets are effectively used in providing correlated information to the system users.