Sep 29, 2009
VLHMM for Web Applications
It is glad to find that a WWW'09 paper cited my work on VLHMM (variable-length hidden Markov model). In this paper, Towards Context-Aware Search by Learning a Very Large Variable Length Hidden Markov Model from Search Logs, the authors propose to learn a very-large VLHMM for Web user behavior modeling. I also re-visited my old Web page on VLHMM.
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2 comments:
It's indeed a very interesting paper.
However i have some questions please. In this paper, the authors have used a vlhmm instead of a 1-hmm, so the transition probility distribution become P(state si|sequence Sj of states), the question is : what does Sj represent and to model it in the transitions matrix, and for a given state what is the cardinality of Sj.
if you can answer me i would be very grateful.
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