A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is
Frequent Item set Mining is a Data Mining task that has attracted the researchers' interests in a way that very few other tasks have done. This concept is generally used in Decision Support problems. Many serial and parallel algorithms have been developed for Frequent Item set Mining. In this paper, we have focused on the developments of parallel algorithms in this area so far. We start with an Apriori-based parallel algorithm that focuses on minimizing the communication overhead even if, indoi:10.18535/ijsrm/v5i6.34 fatcat:z4jjfuh6rvguji7jjipkxicgkq