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|Title:||Identifying Relationships in Transactional Data|
|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.|
|Appears in Collections:||LIAAD - Book Chapters|
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