1. Nigel Duffy

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      Statistical Methods in Natural Language Processing Michael Collins AT&T Labs-Research Overview Some NLP problems: Information extraction (Named entities, Relationships between entities, etc.) Finding linguistic structure Part-of-speech tagging, ``Chunking'', Parsing Techniques: Log-linear (maximum-entropy) taggers Probabilistic context-free grammars (PCFGs) PCFGs with enriched non-terminals Discriminative methods: Conditional MRFs, Perceptron algorithms, Kernel methods
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    3. Machine Learning Methods in Natural Language Processing

      Machine Learning Methods in Natural Language Processing Michael Collins MIT CSAIL Some NLP Problems Information extraction -- Named entities -- Relationships between entities Finding linguistic structure -- Part-of-speech tagging -- Parsing Machine translation Common Themes Need to learn mapping from one discrete structure to another -- Strings to hidden state sequences Named-entity extraction, part-of-speech tagging -- Strings to strings Machine translation -- Strings to underlying
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    4. Parameter Estimation for Statistical Parsing Models: Theory andPractice of Distribution-Free Methods.

      Chapter 1 PARAMETER ESTIMATION FOR STATISTICAL PARSING MODELS: THEORY AND PRACTICE OF DISTRIBUTION-FREE METHODS Michael Collins MIT Computer Science and Artificial Intelligence Laboratory 200 Technology Square, Cambridge, MA 02193, USA mcollins@ai.mit.edu Abstract A fundamental problem in statistical parsing is the choice of criteria and algorithms used to estimate the parameters in a model. The predominant approach in computational linguistics has been to use a parametric model with ...
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      Discourse, Entailment, Machine Translation, NER, Parsing, Segmentation, Semantic, Sentiment, Summarization, WSD