Class Schedule

Week 1 – 31 August

• Intro to Computational Linguistics
• Intro to course logistics
• Stream – collaborative decision
• Text Analysis for Digital humanities (see Resources for Digital Humanities)

Week 2 – 7 September

• Discussion of the following articles:
• The End of Theory: The Data Deluge Makes the Scientific Method Obsolete by Chris Anderson
• Visualizing Big Data: Bar Charts for Words by Mark Horowitz
• Scan This Book! by Kevin Kelly
• Google’s Moon Shot by Jeffrey Toobin
• Quantitative Analysis of Culture Using Millions of Digitized Books 
• Matthew Jocker’s critique of the Google’s ngram analyzer
• Text Analysis Continued
• Discussion of results with tools
• Introduction to Morphology  (PDF of slides)
• Introduction to Finite State Transducers

Week 3 – 14 September

• Southern Brazilian Portuguese Pronunciation
• worksheet
• data (pdf)
• How Natural Language Processing is Changing – a video
• Entropy and Entropy Worksheet on Rotokas.
• Discussion of the debate between Peter Norvig, Director of Research at Google and Noam Chomsky.
• On Chomsky and the Two Cultures of Statistical Learning by Peter Norvig. (everyone read) First responders: Brian, Shannon
• Norvig vs. Chomsky and the Fight for the Future of AI by Kevin Gold. First Responder: Samantha
• Discussion of the following article:
• Unsupervised Learning of the Morphology of a Natural Language  by John Goldsmith. First Responder: Mary
• ToDo: Download and install Linguistica and test it on how well it learns morphology of a corpus of English that you find and a corpus of another language.
• Computational Morphology continued

Week 4 – 21 September

• Discussion of Morphology long-term HW – Finite State Transducers and Morphology (link to write-up)
• Discussion of Joint Entropy of Rotokas  and other langs (Please compute this before class)
• Southern Brazilian Portuguese FST  (15 min)
• English Plurals FST   (15 min)
• Unsupervised Morphology (20 min)
• Demo – Naive Bayes Classifier (zip file of classifier)
• Geographic Classification of Arabic.
• HW for next week (can do with a partner):
• try the classifier on your texts.
• try Linguistica on a Foreign Language Corpus. Analyze results.
• skim Parts of Speech and Basic Syntax chapters of book mentioned in Week 5.

Week 5 – 28 September

• What we learned from 5 million books – TedTalk
• Wrap up and discussion
• Entropy – interested in hearing reports and impressions from people
• Southern Brazilian Portuguese
• English Plurals
• Linguistica – discussion
• Introduction to Lexc – Part of the Xerox Toolkit (pdf of relevant chapter in Finite State Morphology (51MB dl))
• Esperanto Worksheet (2 tasks – first write FSA then FST)
• Linguists in class:
• Parts of Speech  (any intro to Linguistics book or through 5.3 of this chapter)  user:compling/pw – a 1337 version of chomsky (only 1 character changed)  Mary
• Basic Syntax   (any intro to Linguistics book or chapter 12 of  this) Shannon
• Phrase Structure Grammar  and parsing (chapter 13 of  this)

Week 6 – 5 October

• WordSeer – How Natural Language Processing is Changing Research
• Eserpanto Worksheet- finish up FSA and FST
• Talk and demo of Porter Stemmer (info at Martin Porter’s Porter Stemming Algorithm webpage)
• Video of Peter Norvig talking about the effectiveness of data. Either
• Statistical Learning as the Ultimate Agile Development Tool
• The Unreasonable Effectiveness of Data
• Great Programming Shootout
• classify2.py
• Parsing Intro.

Week 7 – 12 October

• Great Classifier ShootOut
• Country / Blues Data Pack
• Guarani / English Data Pack
• Parsing
• Grammars, Parsers, & the CYK algorithm (pdf of slides)
• BUBS parser (please download)
• try it first with the included Berkeley grammar
• the simple2.gr.txt file
• rule format discussion
• parsing worksheet
• try entering the Wumpus grammar 

Week 8 – 19 October

• Game plan for rest of semester
• Introduction to the Final Project (pdf of slides)
• Great Classifier ShootOut
• BUBs parser lab
• Statistical Machine Translation I: Word Alignment Models (Kevin Knight’s A Statistical MT Tutorial Workbook (rtf)
• Language Model Optional Project (description)
• texts to unscramble: Walden-scrambled (for testing), Enron Email

Week 9 – 26 October

• Project elevator pitch
• 15-20 minute presentation Ferrucci et al. Building Watson: An Overview of the DeepQA Project, AI Magazine 2010: Ryan and Shannon!
• 15-20 minute presentation AskMSR question answering system (report on both AskMSR: Question Answering Using the Worldwide Web and  An Analysis of the AskMSR Question-Answering System)  Ashby & Valerie!
• time to co-ordinate project
• Statistical Machine Translation II: Statistical Alignment Models (chapter 25 of this draft)
• Videos shown in class:
• The Bears discuss the state of the machine learning labor market.
• Machine learning of language – a lecture by Christopher Manning.

Week 10 – 2 November

• Project update reports
• Discussion of Manning Video
• Information Extraction presentation (chapter 22 intro through 22.1 Named Entity Extraction of this draft same pw as above) student presenter 10 minutes. Gray & Eric!
• Information Extraction presentation (chapter 22 —  section 22.2 of this draft)  Joe F and Jacob B!
• Introduction to Information Extraction Technology (old paper but still relevant) Amy Olson & Samantha Whay
• 1/2 hr. to co-ordinate project
• Odds and Ends re. Satistical MT
• Evaluating MT systems
• Hands-on MT lab  (going through basic tutorial (sec 2.1) of Moses Statistical Machine Translation System User Manual.

Week 11 – 9 November

• Sprint 1 demo (5 – 10 minutes each team)
• Intro to Computational Semantics
• Computers versus Common Sense (The Cyc Project) Doug Lenat vido
• Hands-on MT lab.  (handout)

Week 12 – 16 November

• Sprint 2 demo (5 – 10 minutes each team)
• Computers versus Common Sense (The Cyc Project) Doug Lenat
• Semantic Role Labeling (if people need it, can make this a student presentation, let me know)

Week 13 – 23 November

• Thanksgiving Break

Week 14 – 30 November

• Cyc Discussion
• OpenCyc
• Open Cog Project (talk by Ben Goertzel)
• Formal Computational Semantics
• Soft AI: what we have now: Powerset Demo Video
• Hard AI: Embodied Conversational Agents – Justine Cassell’s research
• PBS Scientific American Frontiers (Friendly Characters)
• excerpts from The Human at the Heart of our Work (around the 26 minute mark for code switching and 48 min. for work on autism)
• Apple Knowledge Navigator revisited (vs. annoying Microsoft Paper Clip)
• presentation: The MIT START question answering system. Draw presentation from several papers at http://groups.csail.mit.edu/infolab/publications/ and give demo. (2 presenters)

Week 15 – 7 December

• Final Sprint Demo – 20 minute presentations