clickb
Web Data Analysis by Bayesian Mixture of Markov Models
Designed for web usage data analysis, it implements tools to process web sequences and identify web browsing profiles through sequential classification. Sequences' clusters are identified by using a model-based approach, specifically mixture of discrete time first-order Markov models for categorical web sequences. A Bayesian approach is used to estimate model parameters and identify sequences classification as proposed by Fruehwirth-Schnatter and Pamminger (2010)
- Version0.1
- R versionunknown
- LicenseMIT
- Licensefile LICENSE
- Needs compilation?No
- Last release02/13/2023
Team
Furio Urso
Reza Mohammadi
Show author detailsRolesAuthorAntonino Abbruzzo
Show author detailsRolesAuthorMaria Francesca Cracolici
Show author detailsRolesAuthor
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- Imports4 packages
- Suggests1 package