PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Giannotti F., Gozzi C., Manco G. Clustering transactional data. Internal note CNUCE-B4-01-004, 2001.
 
 
Abstract
(English)
This paper presents a partitioned method which crosses the limitations of traditional approaches to clustering of transactional data. A modification of the stanard K-Means algorithm is presented, which has a good scalability on the number of objects and attributes, but can only work with numeric vectors of fixed length.
Subject Transactional data clustering
K-Means Algoritm
H.3.3 Clustering


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