Title
Cartification : from similarities to itemset frequencies Cartification : from similarities to itemset frequencies
Author
Faculty/Department
Faculty of Sciences. Mathematics and Computer Science
Publication type
article
Publication
Subject
Mathematics
Computer. Automation
Source (journal)
Lecture notes in computer science
Volume/pages
7278(2012) , p. 4-
ISSN
0302-9743
Carrier
E
Target language
English (eng)
Full text (Publishers DOI)
Affiliation
University of Antwerp
Abstract
Suppose we are given a multi-dimensional dataset. For every point in the dataset, we create a transaction, or cart, in which we store the k-nearest neighbors of that point for one of the given dimensions. The resulting collection of carts can then be used to mine frequent itemsets; that is, sets of points that are frequently seen together in some dimensions. Experimentation shows that finding clusters, outliers, cluster centers, or even subspace clustering becomes easy on the cartified dataset using state-of-the-art techniques in mining interesting itemsets.
Handle