HAL will be down for maintenance from Friday, June 10 at 4pm through Monday, June 13 at 9am. More information
Skip to Main content Skip to Navigation
Conference papers

Personalisation in Service-Oriented Systems Using Markov Chain Model and Bayesian Inference

Abstract : In the paper a personalization method using Markov model and Bayesian inference is presented. The idea is based on the hypothesis that user’s choice of a new decision is influenced by the last made decision. Thus, the user’s behaviour could be described by the Markov chain model. The extracted knowledge about users’ behaviour is maintained in the transition matrice as probability distribution functions. An estimation of probabilities is made by applying incremental learning algorithm which allows to cope with evolving environments (e.g. preferences). At the end an empirical study is given. The proposed approach is presented on an example of students enrolling to courses. The dataset is partially based on real-life data taken from Wrocław University of Technology and includes evolving users’ behaviour.
Document type :
Conference papers
Complete list of metadata

Cited literature [16 references]  Display  Hide  Download

Contributor : Hal Ifip Connect in order to contact the contributor
Submitted on : Friday, July 21, 2017 - 11:25:15 AM
Last modification on : Friday, July 21, 2017 - 11:34:17 AM


Files produced by the author(s)


Distributed under a Creative Commons Attribution 4.0 International License



Jakub Tomczak, Jerzy Świątek. Personalisation in Service-Oriented Systems Using Markov Chain Model and Bayesian Inference. 2nd Doctoral Conference on Computing, Electrical and Industrial Systems (DoCEIS), Feb 2011, Costa de Caparica, Portugal. pp.91-98, ⟨10.1007/978-3-642-19170-1_10⟩. ⟨hal-01566550⟩



Record views


Files downloads