'Dt nn' diaporamas de présentation

CS 2750: Machine Learning Hidden Markov Models

CS 2750: Machine Learning Hidden Markov Models. Prof. Adriana Kovashka University of Pittsburgh March 21, 2016 All slides are from Ray Mooney. Motivating Example: Part Of Speech Tagging. Annotate each word in a sentence with a part-of-speech marker. Lowest level of syntactic analysis.

1.16k views • 113 slides

Knowledge Extraction based on Discourse Representation Theory and Linguistic Frames

489 views • 45 slides

Unsupervised Dependency Parsing

Unsupervised Dependency Parsing. David Mare ?ek Institute of Formal and Applied Linguistics Charles University in Prague Doctoral thesis defense September 26, 2012. Outline. Unsupervised dependency parsing What is it? What is it good for? My work Reducibility feature Dependency model

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Unsupervised Learning of Soft Patterns for Generating Definitions from Online News

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Prototype-Driven Grammar Induction

Prototype-Driven Grammar Induction. Aria Haghighi and Dan Klein Computer Science Division University of California Berkeley. Grammar Induction. DT NN VBD DT NN IN NN The screen was a sea of red. First Attempt. DT NN VBD DT NN IN NN

449 views • 31 slides

Exploiting Reducibility in Unsupervised Dependency Parsing

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Introduction to Machine Learning and Text Mining

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Introduction The Structured Language Model(SLM)

ended. VP. with. PP. loss. NP. of. contract. PP. NP. cents. NP. loss. NP. Speech Recognizer (Baseline LM). Rescoring (New LM). 100 Best Hyp. Speech. 1 hypothesis. Smoothing Issues in the Strucutred Language Model.

61 views • 1 slides