Hidden Markov Model Based Chunking Sample Clauses

Hidden Markov Model Based Chunking. The HMM is prevalent in pattern recognition and xxxxxxxx xxxx analysis. It represents target words and contextual words in a sentence with different states, and marks values to be extracted based on probability distributions learned from previously collected values and their sentence. Once an HMM is trained, it can be used for evaluation, which estimates the probability score of a labeled sequence, or for decoding, which aims to optimize labeling for a sequence of input data (observations).
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