Mining association rules in hypertext database
de Moura Borges, J.L.C. and Levene, Mark (1998) Mining association rules in hypertext database. In: Agrawal, R. and Stolorz, P.E. and Piatetsky-Shapiro, G. (eds.) Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining. AAAI Press, pp. 149-153.
Abstract
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, and two algorithms to mine such rules are proposed. Extensive experiments with random data were conducted and the results show that, in spite of the worst-case complexity analysis which indicates exponential behaviour, in practice the algorithms’ complexity, measured in the number of iterations performed, is linear in the number of nodes traversed.
Metadata
| Item Type: | Book Section |
|---|---|
| School: | Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences |
| Depositing User: | Sarah Hall |
| Date Deposited: | 08 Jun 2021 11:07 |
| Last Modified: | 09 Aug 2023 12:51 |
| URI: | https://eprints.bbk.ac.uk/id/eprint/44642 |
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