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Understanding Part-of-Speech Tagging in Speech and Language Processing

This chapter delves into Part-of-Speech (POS) tagging, covering rule-based and probabilistic methods like Hidden Markov Models (HMM). It discusses traditional parts of speech such as nouns, verbs, adjectives, and more. POS tagging involves assigning lexical markers to words in a collection to aid in

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Understanding RepeatMasker: Design, Function, and Applications

Explore the architecture and usage of RepeatMasker for identifying and analyzing repetitive sequences in genomic data. Discover the sources of repeat sequence data, how RepeatMasker employs motifs for representation, and the utility of consensus and HMM models.

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Understanding Part-of-Speech Tagging and HMM in Text Mining

Part-of-Speech (POS) tagging plays a crucial role in natural language processing by assigning lexical class markers to words. This process helps in speech synthesis, information retrieval, parsing, and machine translation. With the use of Hidden Markov Models (HMM), we can enhance the accuracy of PO

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Understanding Biomedical Data and Markov Decision Processes

Explore the relationship between Biomedical Data and Markov Decision Processes through the analysis of genetic regulation, regulatory motifs, and the application of Hidden Markov Models (HMM) in complex computational tasks. Learn about the environment definition, Markov property, and Markov Decision

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