Infinite Mixtures of Markov Chains

Publikation: Beiträge in SammelwerkenAufsätze in KonferenzbändenForschungbegutachtet

Authors

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.
OriginalspracheEnglisch
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
ErscheinungsortCham
VerlagSpringer Verlag
Erscheinungsdatum2018
Seiten167-181
ISBN (Print)978-3-319-78679-7
ISBN (elektronisch)978-3-319-78680-3
DOIs
PublikationsstatusErschienen - 2018

DOI

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