lecture 1: introduction - computer sciencekc2wc/teaching/nlp16/slides/01-intro.pdf · lecture 1:...
TRANSCRIPT
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Lecture 1:Introduction
Kai-Wei Chang
CS @ University of Virginia
Couse webpage: http://kwchang.net/teaching/NLP16
1CS6501– Natural Language Processing
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Announcements
Waiting list: Start attending the first few meetings
of the class as if you are registered. Given that
some students will drop the class, some space
will free up.
We will use Piazza as an online discussion
platform. Please enroll.
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Staff
Instructor: Kai-Wei Chang
Email: [email protected]
Office: R412 Rice Hall
Office hour: 2:00 – 3:00, Tue (after class).
Additional office hour: 3:00 – 4:00, Thu
TA: Wasi Ahmad
Email: [email protected]
Office: R432 Rice Hall
Office hour: 4:00 – 5:00, Mon
3CS6501– Natural Language Processing
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This lecture
Course Overview
What is NLP? Why it is important?
What will you learn from this course?
Course Information
What are the challenges?
Key NLP components
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What is NLP
Wiki: Natural language processing (NLP) is
a field of computer science, artificial
intelligence, and computational linguistics
concerned with the interactions between
computers and human (natural) languages.
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Go beyond the keyword matching
Identify the structure and meaning of
words, sentences, texts and conversations
Deep understanding of broad language
NLP is all around us
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Machine translation
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Facebook translation, image credit: Meedan.org
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Statistical machine translation
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Image credit: Julia Hockenmaier, Intro to NLP
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Dialog Systems
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Sentiment/Opinion Analysis
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Text Classification
Other applications?
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www.wired.com
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Question answering
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credit: ifunny.com
'Watson' computer wins at 'Jeopardy'
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Question answering
Go beyond search
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Natural language instruction
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https://youtu.be/KkOCeAtKHIc?t=1m28s
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Digital personal assistant
Semantic parsing – understand tasks
Entity linking – “my wife” = “Kellie” in the phone
book
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credit: techspot.com
More on natural language instruction
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Information Extraction
Unstructured text to database entries
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Yoav Artzi: Natural language processing
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Language Comprehension
Q: who wrote Winnie the Pooh?
Q: where is Chris lived?
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Christopher Robin is alive and well. He is the same
person that you read about in the book, Winnie the Pooh.
As a boy, Chris lived in a pretty home called Cotchfield
Farm. When Chris was three years old, his father wrote
a poem about him. The poem was printed in a magazine
for others to read. Mr. Robin then wrote a book
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What will you learn from this course
The NLP Pipeline
Key components for
understanding text
NLP systems/applications
Current techniques & limitation
Build realistic NLP tools
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What’s not covered by this course
Speech recognition – no signal processing
Natural language generation
Details of ML algorithms / theory
Text mining / information retrieval
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This lecture
Course Overview
What is NLP? Why it is important?
What will you learn from this course?
Course Information
What are the challenges?
Key NLP components
CS6501– Natural Language Processing 20
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Overview
New course, first time being offered
Comments are welcomed
Aimed at first- or second- year PhD students
Lecture + Seminar
No course prerequisites, but I assume
programming experience (for the final project)
basics of probability calculus, and linear
algebra (HW0)
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Grading
No exam & HW -- hooray
Lectures & forum
Participate in discussion (additional credits)
Review quizzes (25%): 3 quizzes
Critical review report (10%)
Paper presentation (15%)
Final project (50%)
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Quizzes
Format
Multiple choice questions
Fill-in-the-blank
Short answer questions
Each quiz: ~20 min in class
Schedule: see course website
Closed book, Closed notes, Closed laptop
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Critical review report
1 page maximum
Pick one paper from the suggested list
Summarize the paper (use you own words)
Provide detailed comments
What can be improved
Potential future directions
Other related work
Some students will be selected to present
their critical reviews
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Paper presentation
Each group has 2~3 students
Picked one paper from the suggested
readings, or your favorite paper
Cannot be the same as critical review report
Can be related to your final project
Register your choice early
15 min presentation + 2 mins Q&A
Will be graded by the instructor, TA, other
students
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Final Project
Work in groups (2~3 students)
Project proposal
Written report, 2 page maximum
Project report (35%)
< 8 pages, ACL format
Due 2 days before the final presentation
Project presentation (15%)
5-min in-class presentation (tentative)
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Late Policy
Credit of 48 hours for all the assignments
Including proposal and final project
No accumulation
No more grace period
No make-up exam
unless under emergency situation
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Cheating/Plagiarism
No. Ask if you have concerns
UVA Honor Code:
http://www.virginia.edu/honor/
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Lectures and office hours
Participation is highly appreciated!
Ask questions if you are still confusing
Feedbacks are welcomed
Lead the discussion in this class
Enroll Piazza
https://piazza.com/virginia/fall2016/cs6501004
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Topics of this class
Fundamental NLP problems
Machine learning & statistical approaches
for NLP
NLP applications
Recent trend in NLP
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What to Read?
Natural Language ProcessingACL, NAACL, EACL, EMNLP, CoNLL, Coling, TACL
aclweb.org/anthology
Machine learningICML, NIPS, ECML, AISTATS, ICLR, JMLR, MLJ
Artificial IntelligenceAAAI, IJCAI, UAI, JAIR
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Questions?
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This lecture
Course Overview
What is NLP? Why it is important?
What will you learn from this course?
Course Information
What are the challenges?
Key NLP components
CS6501– Natural Language Processing 33
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Challenges – ambiguity
Word sense ambiguity
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Challenges – ambiguity
Word sense / meaning ambiguity
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Credit: http://stuffsirisaid.com
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Challenges – ambiguity
PP attachment ambiguity
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Credit: Mark Liberman, http://languagelog.ldc.upenn.edu/nll/?p=17711
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Challenges -- ambiguity
Ambiguous headlines:
Include your children when baking cookies
Hospitals are Sued by 7 Foot Doctors
Iraqi Head Seeks Arms
Safety Experts Say School Bus Passengers
Should Be Belted
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Challenges – ambiguity
Pronoun reference ambiguity
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Credit: http://www.printwand.com/blog/8-catastrophic-examples-of-word-choice-mistakes
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Challenges – language is not static
Language grows and changes
e.g., cyber lingo
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LOL Laugh out loud
G2G Got to go
BFN Bye for now
B4N Bye for now
Idk I don’t know
FWIW For what it’s worth
LUWAMH Love you with all my heart
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Challenges--language is compositional
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Carefully Slide
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Challenges--language is compositional
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小心:
Carefully
Careful
Take
Care
Caution
地滑:
Slide
Landslip
Wet Floor
Smooth
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Challenges – scale
Examples:
Bible (King James version): ~700K
Penn Tree bank ~1M from Wall street journal
Newswire collection: 500M+
Wikipedia: 2.9 billion word (English)
Web: several billions of words
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This lecture
Course Overview
What is NLP? Why it is important?
What will you learn from this course?
Course Information
What are the challenges?
Key NLP components
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Part of speech tagging
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Syntactic (Constituency) parsing
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Syntactic structure => meaning
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Image credit: Julia Hockenmaier, Intro to NLP
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Dependency Parsing
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Semantic analysis
Word sense disambiguation
Semantic role labeling
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Credit: Ivan Titov
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Christopher Robin is alive and well. He is the
same person that you read about in the book,
Winnie the Pooh. As a boy, Chris lived in a
pretty home called Cotchfield Farm. When
Chris was three years old, his father wrote a
poem about him. The poem was printed in a
magazine for others to read. Mr. Robin then
wrote a book
49
Q: [Chris] = [Mr. Robin] ?
Slide modified from Dan Roth
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Christopher Robin is alive and well. He is the
same person that you read about in the book,
Winnie the Pooh. As a boy, Chris lived in a
pretty home called Cotchfield Farm. When
Chris was three years old, his father wrote a
poem about him. The poem was printed in a
magazine for others to read. Mr. Robin then
wrote a book
50
Co-reference Resolution
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Questions?
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