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Students of Computer Science, study E-Commerce as an auxiliary subject. these are the key points discussed in these Lecture Slides of E-Commerce : Hidden Markov, State Corresponds, Author Name, State Diagram, Observations, Probability Distribution, Possible Words, Specific Distr, Viterbi Algorithm, Bootstrapped
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Each state corresponds to one of the fields that we wish toextract
e.g. paper title, author name, etc. - True Markov state diagram is unknown at parse-time - can see noisy observations from each state - the sequence of words from the document - Each state has a characteristic probability distribution overthe set of all possible words - e.g. specific distribution of words from the state ‘title’ Docsity.com
parse the observed sequence into a corresponding setof inferred states
Viterbi algorithm
in supervised manner with manually labeled data
bootstrapped using a combination of labeled andunlabeled data Docsity.com
