Enhancing the apriori algorithm for frequent set counting
Orlando S., Palmerini P., Perego R.
Knowledge discovery Database Applications. Data mining
In this paper we propose DCP, a new algorithm for solv- ing the Frequent Set Counting problem, which enhances Apriori. Our goal was to optimize the initial iterations of Apriori, i.e. the most time consuming ones when datasets characterized by short or medium length frequent patterns are considered. The main improvements regard the use of an innovative method for storing candidate set of items and counting their support, and the exploitation of eective pruning techniques which signicantly reduce the size of the dataset as execution progresses.
Source: Data Warehousing and Knowledge Discovery, Third International Conference, pp. 71–82, Munich, Germany, 5-7 september 2001
Publisher: Springer, Berlin , Germania
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@inproceedings{oai:it.cnr:prodotti:91446,
title = {Enhancing the apriori algorithm for frequent set counting},
author = {Orlando S. and Palmerini P. and Perego R.},
publisher = {Springer, Berlin , Germania},
booktitle = {Data Warehousing and Knowledge Discovery, Third International Conference, pp. 71–82, Munich, Germany, 5-7 september 2001},
year = {2001}
}
0000-0001-7189-4724