Mining association rules in hypertext databases
José Luís Borges, Mark Levene · 1998
Association rule techniques traditionally aim to mine information from databases consisting of a set of flat transaction records. In this work we propose a generalisation of the notion of association rule in the context of flat transactions to that of a composite association rule in the context of a structured directed graph, such as the world-wide-web. The techniques proposed aim at finding patterns in the user behaviour when traversing such a hypertext system. We redefine the concepts of confidence and support for composite association rules, which are trails of links representing a user's navigation session; the actual data may be obtained from log files. Two algorithms to mine composite association rules are exhibited: one is a modification of the directed graph Depth-First-Search algorithm, and the other uses an incremental approach to build the set of composite rules of size n+ 1 from the set of composite rules of size n. Extensive experiments with random data were conducted in o...