Authors: Bay Vo; Hien T. Nguyen
Addresses: Faculty of Information Technology, Ton Duc Thang University, 19 Nguyen Huu Tho, Tan Phong Ward, District 7, Ho Chi Minh City, Vietnam ' Faculty of Information Technology, Ton Duc Thang University, 19 Nguyen Huu Tho, Tan Phong Ward, District 7, Ho Chi Minh City, Vietnam
Abstract: This paper proposes an algorithm for mining frequent closed itemsets from multidimensional databases. The algorithm, which does not require transforming a database into a transaction database, is based on the intersections of object identifications for fast computing the supports of itemsets. Experimental results show that the algorithm is faster than dCHARM (when transformation of multidimensional databases into transaction databases is included).
Keywords: association rules mining; attributes itemset object; AIO tree; frequent itemsets; frequent closed itemsets; FCIs; multidimensional databases; MDBs; data mining.
International Journal of Computational Vision and Robotics, 2015 Vol.5 No.3, pp.217 - 230
Received: 25 Jun 2013
Accepted: 06 Dec 2013
Published online: 20 Aug 2015 *