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CSE 597 Spring 2019Natural Language Processing
Rebecca (Becky) J. PassonneauSyllabus
Time: Tue/Thu 12:05-1:20Location: Email: Canvas email for class business PSU email for non-class matters [email protected] hours: By appointment
Course announcement textNatural Language Processing is a subfield of artificial intelligence that has been heavily influenced by machine learning. This course will present topics in natural language processing to illustrate the wide range of methods that have been adopted to make human language computable, and the limitations of those methods for different sources of meaning, and different contexts. How we interpret what someone has said or written depends on multiple sources of meaning: the meanings of the individual words; the grammatical relationships among the words; the meanings of what was said or written immediately beforehand; the purposes of the speaker and listener, or author and reader; common-sense knowledge; and so on. Students who take the class will complete homework assignments, solve in-class problems, and develop a project.
2CSE 597 Spring 2019 Natural Language Processing
Format● Two class projects summarized in single final report
○ Pairs of students: replicate RDF to NLG model (Weeks 5-9)○ Teams of 4-6 students: improve the model, or, develop neural summarizer
● Three to four homework programming assignments (Python 2.7)● Twenty-five classes with reading assignments (approximate)
○ Prepare the reading BEFORE the class where we discuss the reading○ Bring questions that show you have done the reading○ Later in the class, students will prepare the class presentations
● Final exam● Piazza● Canvas
3CSE 597 Spring 2019 Natural Language Processing
ReadingsTwo textbooks in pdf/online; copies on Canvas
● Jurafsky, Daniel and James H. Martin. Speech and Language Processing (3rd ed. Draft online) (J&M)
● Goldberg, Joav. 2017. Neural Network Methods for Natural Language Processing (Goldberg)
Additional readings in pdf available on Canvas
● Many taken from an NLP course taught by Noah Smith at University of Washington● Other course syllabi also available
4CSE 597 Spring 2019 Natural Language Processing
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Syllabus Schedule - Weeks 1-8
5CSE 597 Spring 2019 Natural Language Processing
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Syllabus Schedule - Weeks 9-15
6CSE 597 Spring 2019 Natural Language Processing
Course Grade
● Project: 45%● Project presentation: 10%● Homework: 25%● Final: 20%
7CSE 597 Spring 2019 Natural Language Processing
Course Genealogy: Other courses consultedSee “Other Syllabi” in Canvas/Files● Allen Black, Carnegie Mellon University, 2017● Kathleen McKeown, Columbia University, 2017● William Wang, UC Santa Barbara, 2017● Julia Hockenmaier, UI Urbana-Champaign, 2017● Andrew McCallum, U Mass, 2007● Brendan OConnor, U Mass, 2017● Ray Mooney, U Texas, 2017● Yejin Choi, U Washington, 2017● Noah Smith, U Washington, 2016● Ellen Riloff, U Utah, 2017
8CSE 597 Spring 2019 Natural Language Processing
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9CSE 597 Spring 2019 Natural Language Processing
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1010CSE 597 Spring 2019 Natural Language Processing
