Lexicalized HMM

A Lexicalized HMM is an Hidden Markov Model that contains transitions states based on a Lexicon.

• AKA: Lexicalized Hidden Markov Model.
• Context:
  • It can be a Part-of-Speech Tagger.
• See: Lexicalized PCFG.

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References

2009

• (Jin et al., 2009) ⇒ Wei Jin, Hung Hay Ho, Rohini K Srihari. (2009). “OpinionMiner: A Novel Machine Learning System for Web Opinion Mining and Extraction.” In: Proceedings of ACM SIGKDD Conference (KDD-2009). doi:10.1145/1557019.1557148.

2000

• (Lee et al., 2000) ⇒ Sang-Zoo Lee, Jun'ichi Tsujii, and Hae-Chang Rim. (2000). “Lexicalized Hidden Markov Models for Part-of-Speech Tagging.” In: Proceedings of the 18th International Conference on Computational Linguistics (COLING 2000). doi:10.3115/990820.990890.

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