A New Method for User Dynamic Clustering Based on HSMM in Model of SaaS

This paper deeply studies the phenomenon of hard to satisfy the user's personalized services and only a few researches on users themselves in the model of Software as a Service (SaaS), then proposes a users' behavior feature extraction model based on Hidden Semi-Markov Models (HSMM) to solve the problem of getting users hidden information on SaaS platform first. The model uses the probability distribution of state duration time to control user's browsing behaviors, combines hidden states which describe features with time relativity, and applies improved Viterbi algorithm to get user features sequence.

Provided by: zhejiang dali technology co.,ltd Topic: Cloud Date Added: May 2013 Format: PDF

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