CS6501 Information Retrieval Course Policy

CS6501
Advanced Topics in Information Retrieval
Course Policy
Hongning Wang
CS@UVa
Goal of this course
• Discuss fundamental problems in information retrieval
– Building blocks of search engine systems
– Wide coverage of important IR techniques
• Personalized recommendation
• Online advertising
• Get hands-on experience by developing practical
systems/components
• Prepare students for doing cutting-edge research in
information retrieval and related fields
– Open the door to the amazing job opportunities in IT industry
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Character of this course
• Discussion oriented
– This is how great ideas are created!
– You are encouraged to express your thoughts,
confusions, and suggestions
– Focusing on why, rather than how
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Prerequisites
• Programming skills – Important!
– Basic data structures: CS 2150 or equivalent
– Java is required for machine problems
• Most open source packages are written in Java
– Any language you choose for the rest of this course
– Linux system!
• Math background
– Probability
• Discrete/continuous distributions, expectation, moments
– Linear algebra
• Vector, matrix, dot product
– Optimization
• Gradient-based methods
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Pop-up quiz
1. Let a=(1,2,3) and b=(2,3,-2), the inner
product between a and b is
(a) 0
(b) 1
(c) 2
(d) 3
1 2
2. Let A = (
), what is A-1,
2 1
(a) (
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−1 −2
) (b)
−2 −1
1
−
( 23
3
2
3
−
1) (c) (
3
CS6501: Information Retrieval
1 0
2
) (d) (
0 1
1
1
)
2
5
Pop-up quiz
3. What is the expectation of random variables
drawn from Gaussian distribution N(0, 1),
(a) 0
(b) 0.5
(c) 1
(d) 2
4. A biased coin with P(head)=0.2, in a
sequence of 10 consecutive tossing, you have
already got 9 tails, what is the probability you
will have a head at the 10th tossing,
(a) 0
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(b) 0.1
(c) 0.2
CS6501: Information Retrieval
(d) 0.2*0.89
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Pop-up quiz
1. Let a=(1,2,3) and b=(2,3,-2), the inner
product between a and b is (c)
(a) 0
(b) 1
(c) 2
(d) 3
1 2
2. Let A = (
), what is A-1,
2 1
(a) (
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−1 −2
) (b)
−2 −1
1
−
( 23
3
2
3
−
1) (c) (
3
CS6501: Information Retrieval
(b)
1 0
2
) (d) (
0 1
1
1
)
2
7
Pop-up quiz
3. What is the expectation of random variables
drawn from Gaussian distribution N(0, 1), (a)
(a) 0
(b) 0.5
(c) 1
(d) 2
4. A biased coin with P(head)=0.2, in a (c) (d)
sequence of 10 consecutive tossing, you have
already got 9 tails, what is the probability you
will have a head at the 10th tossing,
(a) 0
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(b) 0.1
(c) 0.2
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(d) 0.2*0.89
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Structure of this course
• Six major topics will be covered by lectures
– E.g., Search engine architecture, retrieval models,
search evaluation, relevance feedback, and link
analysis
• Latest development will be covered by
workshop-style paper presentations
– E.g., mobile search, recommendation,
personalization, you name it!
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Grading policy
• Homework (20%)
No curving will be applied!
– Machine problems (~2)
• Quizzes (15%)
– Check points of key concepts (~4)
• Panel discussion (10%)
• Paper presentation (20%)
• Course project (35%)
fairness will be
guaranteed by the
instructor
– In the exam week
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Quiz
• 15 minutes in class
• Format
– True/False questions
– Multiple choice questions
– Short answer questions
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Panel discussion
• Share your opinions on information retrieval
in real world
– Facebook messenger’s new feature
– Google Now’s future
– Reasons of Yahoo’s decline
– Next era of IR
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Paper presentation
• You teach us the latest development in the
field
– Present high-quality research papers published in
the top IR conferences in the past three years
– Lead the discussion about the paper you choose
– Give your comments and thoughts about it
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Course project
• Topics
– Implement algorithms in assigned research papers
– Self-selected topics with permission from the
instructor
• Team work
– 2-3 students per group
• Evaluation
– Two-page proposal (25%)
– 25-minutes in-class presentation (40%)
– Written report (35%)
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Late policy
• Homework
– Submit via Collab (no extension)
– Late penalty: 15%, two weeks after the due date;
50%, afterwards
• Course project
– Final report is due before presentation (no
extension)
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Classroom participation
• HIGHLY APPRECIATED!
– Helps me quickly remember your names
– Reminds me what is still confusing
– You can drive the lecture/discussion in this class!
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Contact information
• Lecture
– Instructor: Hongning Wang
– Time: Tuesday/Thursday 12:30pm to 1:45pm
– Location: Rice Hall 340
• Office hour
– Time: Wednesday 10:00am to 11:00am
• Location: Rice Hall 408
• Course website
– Website:
http://www.cs.virginia.edu/~hw5x/Course/IR2017/_site
– Piazza:
https://piazza.com/virginia/spring2017/cs6501s12/home
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Thank you!
QUESTIONS?
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