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Friday, August 05, 2011

Natural Language Processing


Natural Language Processing

Course description:This course will cover traditional material, as well as recent advances in the theory and practice of natural language processing (NLP) - the creation of computer programs that can understand, generate, and learn natural language. The course will introduce both knowledge-based and statistical approaches to NLP, illustrate the use of NLP techniques and tools in a variety of application areas, and provide insight into many open research problems.


class notes
Lecture
Reading material
Course overview [ppt]
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Short Perl tutorial (I) [ppt]
One of the tutorials below [see the "Links" section]
Short Perl tutorial (II) [ppt]
One of the tutorials below [see the "Links" section]
Linguistics Essentials [ppt] 
Guest lecture by Ben Leong
Chap.3 [Manning & Schutze] or any book on English grammar
Language Models [ppt]
Chap.4 [Jurafsky & Martin]
Language Models [ppt]
Chap.4 [Jurafsky & Martin]
Language Models [ppt]
Chap.4 [Jurafsky & Martin]
Collocations [ppt]
Word classes and part of speech tagging ppt]
Chap.5 [Jurafsky & Martin]
Word classes and part of speech tagging ppt]
Chap.5 [Jurafsky & Martin]
HMM Tagging. Viterbi Algorithm. [ppt]
Chap.6 [Jurafsky & Martin]
Context Free Grammars [ppt] 
Chap.12-13 [Jurafsky & Martin]
Parsing with Context Free Grammars [ppt]
Chap.12-13 [Jurafsky & Martin]
Probabilistic Parsing [ppt] 
Guest lecture by Michael Mohler.
Chap.14 [Jurafsky & Martin]
Presentation and Workshop: "New Google Tools for Research"
Mano Marks, Google
 
Willis 136, first floor of Library
11:30am-2pm
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Exam preparation.
All the material studied so far.
Exam I.
All the material studied so far.
Word Sense Disambiguation [ppt]
Chap. 19, 20 [Jurafsky & Martin]
Word Sense Disambiguation [ppt]
Chap.19, 20 [Jurafsky & Martin]
Word Sense Disambiguation [ppt]
Chap.19, 20 [Jurafsky & Martin]
No class.
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Word Sense Disambiguation
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Special topics: Subjectivity and sentiment analysis [ppt]
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Special topics: Subjectivity and sentiment analysis [ppt]
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Special topics: Text semantic similarity [ppt]
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Special topics: Text classification [ppt]
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Thanksgiving. No class.
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Wrap-up. Project discussions. Exam II preparation.
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Exam II.
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Project presentations.
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Project presentations.
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