LING 83800 - Methods in Computational Linguistics II

Spring 2011
Friday 9:30am - 11:30am
GC 7314
Instructor: Andrew Rosenberg (andrew_at_cs.qc.cuny.edu)
Office Hours: Friday 4:00pm-5:00pm GC 4420

This is the second of a two-part course sequence to train students with a linguistics background in the core methodologies of computational linguistics. Successful completion of this two-course sequence will enable students to take graduate-level elective courses in computational linguistics; both courses are offered by the Graduate Center's Linguistics Program, as well as courses offered by the Computer Science Program. This course will provide training in: the use of computational libraries built specifically for computational linguistics, the techniques used in performing computational analyses of electronic natural language corpora, and the foundational mathematics, probabilistic methods and statistics that are the backbone of modern computational linguistics. The course will go significantly beyond a survey of these topics. By completing the Methods in Computational Linguistics sequence, at the end of the first year, Computational Linguistics Master's students will have the skills they need to engage in further study of state-of-the-art topics in natural language processing.
Successful completion of Methods in Computational Linguistics I is a pre-requisite for this course.

Natural Language Processing with Python by Steven Bird, Ewan Klein and Edward Loper. O'Reilly.
ISBN: 978-0596516499
Also available online at: http://www.nltk.org/book
This should be available through the bookstore, but may be found through other outlets at a discount.

Come to Class. It will be difficult to do well in the class without regular attendance. There is no additional penalty for missing class.

Cell phones must be on silent, and are not to be checked or used during class - if you are expecting an urgent call, tell the instructor at the start of class.

Laptops, tablets or lab computers are welcome in class. There will be some interactive exercises..

Cell phone and Laptop policy: One warning, after that 5 points off the next homework for each issue. Same policy for the instructor. One warning, after that, everyone gets 5 points on the next homework.

The Final Letter Grade will be based on a scaled adjustment of the Final Numeric Grade. When the scale has been determined, the class will be informed either in class or over email, and it will be posted to the course webpage (here).

Do not cheat. You may discuss assignments with your classmates, but write or program your assignment alone. Do not ask for or offer to share code, or written assignments. If you discuss an assignment with a classmate, or on an online forum, include the name of the classmate or URL of the forum on your assignment or in the documentation of your code. The first instance of cheating results in an automatic zero for the assignment (or final project). A second instance of cheating results in a zero (F) for the course. The Computer Science Department will be notified in writing of all instances of cheating. On a second instance a report will be submitted to the Office of Academic Integrity.

Assignments will be posted to the website (here) after class the date that they are assigned.

There are 5 assignments. Each assignment will have a theoretical (pen-and-paper) component. Assignments may also include an implementation (coding) component.

Assignments will be due by 11:59pm on their due date. Assignments should be delivered electronically, via email.

Deliver assignments with a timestamp before 11:59pm on the due date to avoid a late penalty. If an extension is needed let me know as soon as possible. I will do my best to be reasonable to you and fair to the rest of class.

In extenuating circumstances, students may be given an Incomplete if material has not been completed by the end of the semester. When an incomplete is granted, the student and instructor will specify, in writing, a timeframe for all outstanding material to be submitted. If no other timeframe has been specified in writing, the deadline for all outstanding material to be submitted to resolve an incomplete will be one month following the last meeting of the class. This semester, that would make the deadline: June 18. An incomplete that is not resolved by the deadline will become an F

Students are expected to attend three CUNY-NLP seminars and write a 2 page summary of the speaker's talk. This summary should include: 1) The topic and motivation of the work, 2) a description of the approach discussed, 3) a critical response to the work: major strengths and weaknesses, potential improvements or other applications of the approach.

Schedule

Date	Material (Tentative)	Assignments
Friday, January 27	No Class.
Friday, February 3	Welcome. Introduction to NLTK. Sorting and Searching. [pptx]	Read Chapter 1 of NLTK book.
Friday, February 10	Counting Things: Probability, Bayes Rule. NLTK: FreqDist [pptx]
Friday, February 17	Counting More Things. Conditionals NLTK: ConditionalFreqDist [pptx]	Homework 1 Assigned
Friday, February 24	Matching Things Regular Expressions.
Friday, March 2	Annotating Things Corpus Construction. Part-of-speech tagging Parsing More Regular Expressions [pptx] [idle output] [demo python code]	Homework 1 Due
Friday, March 9	Relating Things Assessing word similarity WordNet Co-occurences Word classes List Comprehensions. [pptx] [idle output] [demo python code]	Homework 2 Assigned html files
Friday, March 16	Go to Computational Presentations as part of CUNY 2012.
Friday, March 23	Structuring Things Functions Object Oriented Programming Data structures: 2d lists, trees, graphs. [pptx]	Homework 2 Due Homework 3 Assigned
Friday, March 30	Recursion. Inheritance. Dynamic Programming. [pptx] [inh.py] [tree.py] [shape.py] [class_example.py]	Homework 3 Due on April 2
Friday, April 6	No Class: Spring Recess
Friday, April 13	No Class: Spring Recess
Friday, April 20	Classifying Things Machine Learning in Computational Linguistics Using NLTK classification routines. Evaluation key demo code	Homework 4 Assigned
Friday, April 27	Part-of-speech Tagging Dictionaries Training a Tagger in NLTK key
Friday, May 4	Dynamic Programming Minimum Edit Distance key fibonacci example making change example minimum edit distance example	Homework 5 Assigned. Homework 4 Due
Friday, May 11	Last Day of Class Plotting and Graphics with nltk and matplotlib Segmentation. Textual Entailment. key examples
Tuesday, May 22	No class -- Finals week.	Homework 5 Due