Infinite Mixtures of Markov Chains

Publikation: Beiträge in SammelwerkenAufsätze in KonferenzbändenForschungbegutachtet


Facilitating a satisfying user experience requires a detailed understanding of user behavior and intentions. The key is to leverage observations of activities, usually the clicks performed on Web pages. A common approach is to transform user sessions into Markov chains and analyze them using mixture models. However, model selection and interpretability of the results are often limiting factors. As a remedy, we present a Bayesian nonparametric approach to group user sessions and devise behavioral patterns. Empirical results on a social network and an electronic text book show that our approach reliably identifies underlying behavioral patterns and proves more robust than baseline competitors.
TitelNew Frontiers in Mining Complex Patterns : 6th International Workshop, NFMCP 2017 : held in conjunction with ECML-PKDD 2017, Skopje, Macedonia, September 18-22, 2017 : revised selected papers
HerausgeberAnnalisa Appice, Corrado Loglisci, Giuseppe Manco, Elio Masciari
Anzahl der Seiten15
ISBN (Print)978-3-319-78679-7
ISBN (elektronisch)978-3-319-78680-3
PublikationsstatusErschienen - 2018