A large-scale hidden semi-Markov model for anomaly detection on user browsing behaviors
IEEE/ACM Transactions on Networking (TON)
Markovian workload modeling for Enterprise Application Servers
C3S2E '09 Proceedings of the 2nd Canadian Conference on Computer Science and Software Engineering
A novel prediction model based on hierarchical characteristic of web site
Expert Systems with Applications: An International Journal
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The significance of modelling and measuring various attributesof the Web in part or as a whole is undeniable. AlthoughWeb related metrics have become increasingly sophisticated,few employ models to explain their measurements.In this paper, we discuss metrics for usage characterization.We considered the application of patterns inbrowsing behavior of users for predicting access to Webdocuments. We proposed two models based on Markov processesfor addressing our specification of the access predictionproblem. The first adapts a stochastic model for librarycirculations, i.e., Morse's model in the context of accessingWeb documents. The second approach can be used fordetermining access probabilities of Webpages within a siteby modelling the browsing process as an ergodic Markovchain.