Another popular approach to modeling users’ goals, intentions, and plans through sequence data is a hidden Markov model (HMM). HMMs have been used in many domains and have seen a lot of success in speech recognition as well as in modeling activities and intent.

Markov networks (MNs)

Markov networks (MNs) are similar to BNs but where the edges are nondirectional. Thus, their inference and learning algorithms are different to accommodate the difference in how knowledge is propagated through the network. HMMs are MNs but with hidden nodes denoting latent variables.

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