Referenced Items are not available for this document.
In this paper we propose a novel methodology for analyzing web user behavior based on session simulation by using an Ant Colony Optimization algorithm which incorporates usage, structure and content data originating from a real web site. In the first place, artificial ants learn from a clustered web user session set through the modification of a text preference vector. Then, trained ants are released through a web graph and the generated artificial sessions are compared with real usage. The main result is that the proposed model explains approximately 80% of real usage in terms of a predefined similarity measure.
Published in:
Web Intelligence and Intelligent Agent Technology (WI-IAT), 2011 IEEE/WIC/ACM International Conference on
(Volume:1
)
Date of Conference: 22-27 Aug. 2011
- Page(s):
- 457 - 464
- E-ISBN :
- 978-0-7695-4513-4
- Print ISBN:
- 978-1-4577-1373-6
- INSPEC Accession Number:
- 12302078
- Conference Location :
- Lyon
- Digital Object Identifier :
- 10.1109/WI-IAT.2011.116
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