Infinite Mixture Model of Markov Chains

Autor: Reubold, Jan, Strufe, Thorsten, Brefeld, Ulf

We propose a Bayesian nonparametric mixture model for prediction- and information extraction tasks with an efficient inference scheme. It models categorical-valued time series that exhibit dynamics from multiple underlying patterns (e.g. user behavio

Externí odkaz: http://arxiv.org/abs/1706.06178

Infinite Mixtures of Markov Chains

Autor: Reubold, Jan, Boubekki, Ahcène, Strufe, Thorsten, Brefeld, Ulf

Publikováno v: Reubold, J, Boubekki, A, Strufe, T & Brefeld, U 2018, Infinite Mixtures of Markov Chains . in A Appice, C Loglisci, G Manco & E Masciari (eds), New 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 . Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10785 LNAI, Springer, Cham, pp. 167-181 . https://doi.org/10.1007/978-3-319-78680-3_12
Reubold, J, Boubekki, A, Strufe, T & Brefeld, U 2018, Infinite Mixtures of Markov Chains . in A Appice, C Loglisci, G Manco & E Masciari (eds), New 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 . Lecture Notes in Computer Science, vol. 10785, Springer, Cham, pp. 167-181 . DOI: 10.1007/978-3-319-78680-3_12

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

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::28c71997365c9142755d0b2936f91316
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