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Title: Identifying Relationships in Transactional Data
Authors: João Gama
Melissa Rodrigues
Carlos Ferreira
Issue Date: 2012
Abstract: Association rules is the traditional way used to study market basket or transactional data. One drawback of this analysis is the huge number of rules generated. As a complement to Association Rules, Association Rules Network (ARN), based on Social Network Analysis (SNA) has been proposed by several researchers. In this work we study a real market basket analysis problem, available in a Belgian supermarket, using ARNs. We learn ARNs by considering the relationships between items that appear more often in the consequent of the Association Rules. Moreover, we propose a more compact variant of ARNs: the Maximal Itemsets Social Network (MISN). In order to assess the quality of these structures, we compute SNA based metrics, like weighted degree and utility of community.
metadata.dc.type: bookPart
Appears in Collections:LIAAD - Book Chapters

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