This paper describes how binary associations in databases of items can be organised and clustered. Two similarity measures are presented that can be used to generate a weighted graph of associations. Each measure focuses on different kinds of regularities in the database. By calculating a Minimum Spanning Tree on the graph of associations, the most significant associations can be discovered and easily visualised, allowing easy understanding of existing relations. By deleting the least interesting associations from the computed tree, the attributes can be clustered.
['Arno J. Knobbe', 'Pieter W. Adriaans']
Analysing binary associations