I. E. Genrikhov, E. V. Djukova, “Mining frequent items in a product of partial orders using parallel calculations”, Avtomat. i Telemekh., 2021, Issue 10,Pages <nobr>13

Mining frequent items in a product of partial orders using parallel calculations

I. E. Genrikhov^a, E. V. Djukova^b

^a Mobile Park, Khimki, Moscow oblast, 141407 Russia
^b Federal Research Center “Computer Science and Control,” Russian Academy of Sciences, Moscow, 119333 Russia

Abstract: We consider the issues of data analysis with items from the Cartesian product of finite partially ordered sets. For efficiently mining frequent items generated by all possible binarization options for the original nonbinary data, we use a modification of the classic FP-tree (Frequent Pattern Tree). Time savings are achieved through the use of parallel computing based on Compute Unified Device Architecture (CUDA) technology. The results of testing the constructed parallel procedures for synthesizing the desired frequent items using model and real data are presented.

Keywords: Cartesian product of partial orders, database, frequent item, FP-tree, threshold FP-tree, parallel computing, CUDA technology.

Presented by the member of Editorial Board: A. A. Lazarev

Received: 24.01.2021
Revised: 05.04.2021
Accepted: 30.06.2021

DOI: 10.31857/S0005231021100032