Borges, J. and Levene, Mark (2004) An average linear time algorithm for web data mining. International Journal of Information Technology and Decision Making 3 (2), pp. 307-320. ISSN 0219-6220.
|
Text
borges_linear_time_hpg.pdf Download (221kB) | Preview |
Abstract
In this paper, we study the complexity of a data mining algorithm for extracting patterns from user web navigation data that was proposed in previous work.3 The user web navigation sessions are inferred from log data and modeled as a Markov chain. The chain's higher probability trails correspond to the preferred trails on the web site. The algorithm implements a depth-first search that scans the Markov chain for the high probability trails. We show that the average behaviour of the algorithm is linear time in the number of web pages accessed.
Metadata
| Item Type: | Article |
|---|---|
| Keyword(s) / Subject(s): | Web usage mining, Markov chains, analysis of algorithms |
| School: | Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences |
| Research Centres and Institutes: | Birkbeck Knowledge Lab |
| Depositing User: | Administrator |
| Date Deposited: | 23 Aug 2005 |
| Last Modified: | 09 Aug 2023 12:28 |
| URI: | https://eprints.bbk.ac.uk/id/eprint/213 |
Statistics
Additional statistics are available via IRStats2.
Archive Staff Only (login required)
