Diversified Hidden Markov Models for Sequential Labeling

5 Apr 2019Maoying QiaoWei BianRichard Yida XuDacheng Tao

Labeling of sequential data is a prevalent meta-problem for a wide range of real world applications. While the first-order Hidden Markov Models (HMM) provides a fundamental approach for unsupervised sequential labeling, the basic model does not show satisfying performance when it is directly applied to real world problems, such as part-of-speech tagging (PoS tagging) and optical character recognition (OCR)... (read more)

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