Hierarchical Hidden Markov Model

A Hierarchical Hidden Markov Model is an Hidden Markov Model that can model a Hierarchical Data Structure.

• AKA: Hierarchical HMM, HHMM.
• See: Dynamic Bayesian Network, Structured Learning Algorithm, Hierarchical Conditional Random Field.

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References

2003

• (Skounakis et al., 2003) ⇒ Marios Skounakis, Mark Craven, and Soumya Ray. (2003). “Hierarchical Hidden Markov Models for Information Extraction.” In: Proceedings of IJCAI Conference (IJCAI 2003).

2001

• (Murphy & Paskin, 2001) ⇒ Kevin P. Murphy, and Mark A. Paskin. (2001). “Linear Time Inference in Hierarchical HMMs.” In: Proceedings of NIPS 2001.

1998

• (Fine et al., 1998) ⇒ Shai Fine, Yoram Singer, and Naftali Tishby. (1998). “The Hierarchical Hidden Markov Model: Analysis and applications.” In: Machine Learning, 32(1). doi:10.1023/A:1007469218079.

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