PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Orlando S., Palmerini P., Perego R. Enhancing the apriori algorithm for frequent set counting. In: DaWaK 2001 - Data Warehousing and Knowledge Discovery : Third International Conference (Munich, Germany, 5-7 september 2001). Proceedings, pp. 71 - 82. (Lecture Notes in Computer Science, vol. 2114). Springer, 2001.
 
 
Abstract
(English)
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 e ective pruning techniques which signi cantly reduce the size of the dataset as execution progresses.
Subject Knowledge discovery
H.2.8 Database Applications. Data mining


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