Requirements

The final grade will be based on problem sets (10%), quizzes (30%), a midterm exam (30%), and a final exam (30%). The problem sets are a small part of the grade, but will be excellent practice for the quizzes and exams. Late homeworks will be accepted (with a grade penalty) for one week only after the deadline. Quizzes will be announced in advance, and I’ll drop the lowest quiz grade. If you can’t make it to a quiz or exam, let me know in advance! There will be no make-up exams without prior arrangements.

Important dates

Mid-term exam: March 12
Final exam: May 12

Readings

The required textbooks for this course are:

Peter Jackson and Isabelle Moulinier. 2007. Natural Language Processing for Online Applications (2nd edition). John Benjamins. http://www.jacksonpeter.com/nlp

and

Department of Linguistics. 2007. Language Files (10th Edtion). Ohio State University Press. http://www.ling.ohio-state.edu/publications/files/

They are for sale in the campus bookstore and at Amazon, etc. Updates and corrections can be downloaded from the authors’ websites. Additional readings will be made available in class or via the “Resources” section of the course web page.

Proposed schedule:

• Week 1 Introduction
  Background · What is computational linguistics? · What’s it good for? · Linguistics
  
• Week 2–4 Processing words
  Regular expressions · Finite state machines · Word structure · Computational morphology
  
• Week 5–6 Processing sounds
  Sound patterns · Phonological and orthographic rules · Speech synthesis
  
• Week 7 Natural language processing
  Tokenization · Corpora · Machine translation
  
• Week 8 Midterm exam 
• Week 9–10 Web searching
  Document retrieval · Spiders · Web scraping · Google
  
• Week 11–12 Information extraction
  Parts of speech · Taggers · Grammars (Context free and beyond)
  
• Week 13–14 Text mining
  Document classification · Spam detection · Data mining · Question answering
  
• Week 15 Review