In this paper we focus on the problem of clustering individual transactional data for a large mass of users. Transactional data is a very pervasive kind of.
We propose txmeans, a parameter-free clustering algorithm able to efficiently partitioning transactional data in a completely automatic way.
Aug 13, 2017 · Once the first scan of the data set is completed, the algorithm performs a few other passes over the data set in order to refine the clustering.
This paper proposestxmeans, a parameter-free clustering algorithm able to efficiently partitioning transactional data in a completely automatic way and ...
KDD Papers. Clustering Individual Transactional Data for Masses of Users. Riccardo Guidotti (University of Pisa); ...
Duration: 3:00
Posted: Jun 28, 2017
Posted: Jun 28, 2017
Title, Clustering Individual Transactional Data for Masses of Users. Publication Type, Conference Paper. Year of Publication, 2017.
Jul 1, 2017 · In this paper we focus on the problem of clustering individual transactional data for a large mass of users. The authors of the paper are ...
In this paper we focus on the problem of clustering individual transactional data for a large mass of users. Transactional data is a very pervasive kind of ...
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This paper presents SCALE, a fully automated transactional clustering framework. The SCALE de- sign highlights three unique features.
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