pick a good ir research problem

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2008 © ChengXiang Zhai Dragon Star Lecture at Beijing University, June 21-30, 2008 1 Pick a Good IR Research Problem ChengXiang Zhai Department of Computer Science Graduate School of Library & Information Science Institute for Genomic Biology, Statistics University of Illinois, Urbana-Champaign http://www-faculty.cs.uiuc.edu/~czhai, [email protected]

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Pick a Good IR Research Problem. ChengXiang Zhai Department of Computer Science Graduate School of Library & Information Science Institute for Genomic Biology, Statistics University of Illinois, Urbana-Champaign http://www-faculty.cs.uiuc.edu/~czhai, [email protected]. - PowerPoint PPT Presentation

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Page 1: Pick a Good IR Research Problem

2008 © ChengXiang Zhai Dragon Star Lecture at Beijing University, June 21-30, 2008 1

Pick a Good IR Research Problem

ChengXiang ZhaiDepartment of Computer Science

Graduate School of Library & Information Science

Institute for Genomic Biology, Statistics

University of Illinois, Urbana-Champaign

http://www-faculty.cs.uiuc.edu/~czhai, [email protected]

Page 2: Pick a Good IR Research Problem

2008 © ChengXiang Zhai Dragon Star Lecture at Beijing University, June 21-30, 2008 2

What is a Good Research Problem?

• Well-defined: Would we be able to tell whether we’ve solved the problem?

• Highly important: Who would care about the solution to the problem? What would happen if we don’t solve the problem?

• Solvable: Is there any clue about how to solve it? Do you have a baseline approach? Do you have the needed resources?

• Matching your strength: Are you at a good position to solve the problem?

Page 3: Pick a Good IR Research Problem

2008 © ChengXiang Zhai Dragon Star Lecture at Beijing University, June 21-30, 2008 3

Challenge-Impact Analysis

Level of Challenges

Impact/Usefulness

Known

UnknownGood applications

Not interestingfor research

High impactLow risk (easy)

Good short-termresearch problems

High impactHigh risk (hard)Good long-term

research problemsDifficult

basic researchProblems,

but questionable impact

Low impactLow risk

Bad research problems(May not be publishable)

Your research proposal

Page 4: Pick a Good IR Research Problem

2008 © ChengXiang Zhai Dragon Star Lecture at Beijing University, June 21-30, 2008 4

How to Find a Problem?

• Application-driven (Find a nail, then make a hammer)

– Identify a need by people/users that cannot be satisfied well currently (“complaints” about current data/information management systems?)

– How difficult is it to solve the problem?

• No big technical challenges: do a startup

• Lots of big challenges: write a research proposal

– Identify one technical challenge as your topic

– Formulate/frame the problem appropriately so that you can solve it

• Aim at a completely new application/function (find a high-stake nail)

Page 5: Pick a Good IR Research Problem

2008 © ChengXiang Zhai Dragon Star Lecture at Beijing University, June 21-30, 2008 5

How to Find a Problem? (cont.) • Tool-driven (Hold a hammer, and look for a nail)

– Choose your favorite state-of-the-art tools • Ideally, you have a “secret weapon”

• Otherwise, bring tools from area X to area Y

– Look around for possible applications

– Find a novel application that seems to match your tools

– How difficult is it to use your tools to solve the problem? • No big technical challenges: do a startup

• Lots of big challenges: write a research proposal

– Identify one technical challenge as your topic

– Formulate/frame the problem appropriately so that you can solve it

• Aim at important extension of the tool (find an unexpected application and use the best hammer)

Page 6: Pick a Good IR Research Problem

2008 © ChengXiang Zhai Dragon Star Lecture at Beijing University, June 21-30, 2008 6

How to Find a Problem? (cont.)

• In practice, you do both in various kinds of ways

– You talk to people in application domains and identify new “nails”

– You take courses and read books to acquire new “hammers”

– You check out related areas for both new “nails” and new “hammers”

– You read visionary papers and the “future work” sections of research papers, and then take a problem from there

– …

Page 7: Pick a Good IR Research Problem

2008 © ChengXiang Zhai Dragon Star Lecture at Beijing University, June 21-30, 2008 7

Three Basic Questions to Ask about an IR Problem

• Who are the users?– Everyone vs. Small group of people

• What data do we have?– Web (whole web vs. sub-web)

– Email (public email vs. personal email)

– Literature (general vs. special discipline)

– Blog, forum, …

• What functions do we want to support?– Information access vs. knowledge acquisition

– Decision and task support

Everyone (who has an Internet connection)

The whole web (indexed by Google)

Search (by keywords)

Page 8: Pick a Good IR Research Problem

2008 © ChengXiang Zhai Dragon Star Lecture at Beijing University, June 21-30, 2008 8

Map of IR Applications

Web pages

News articles

Email messages

Literature

Organization docs

Legal docs/Patents

Medical records

Customer complaint letter/transcripts

KidsPeking Univ. community

Lawyers Scientists

Search Browsing Alert MiningTask/Decision

support

CustomerServicePeople

Email management+ automatic reply

“Google Kids”

Legal InfoSystems

LiteratureAssistant

IntranetSearch

LocalWeb

Service

Blog articles

OnlineShoppers

?

Page 9: Pick a Good IR Research Problem

2008 © ChengXiang Zhai Dragon Star Lecture at Beijing University, June 21-30, 2008 9

High-Level Challenges in IR

• How to make use of imperfect IR techniques to do something useful?

– Save human labor (e.g., partially automate a task)

– Create “add on” value (e.g., literature alert)

– A lot of HCI issues (e.g., allowing users to control)

• How to develop robust, effective, and efficient methods for a particular application?

– Methods need to “work all the time” without failure

– Methods need to be accurate enough to be useful

– Methods need to be efficient enough to be useful

Page 10: Pick a Good IR Research Problem

2008 © ChengXiang Zhai Dragon Star Lecture at Beijing University, June 21-30, 2008 10

Challenge 1: From Search to Information Access

• Search is only one way to access information

• Browsing and recommendation are two other ways

• How can we effectively combine these three ways to provided integrated information access?

• E.g., artificially linking search results with additional hyperlinks, “literature pop-ups”…

Page 11: Pick a Good IR Research Problem

2008 © ChengXiang Zhai Dragon Star Lecture at Beijing University, June 21-30, 2008 11

Challenge 2: From Information Access to Task Support

• The purpose of accessing information is often to perform some tasks

• How can we go beyond information access to support a user at the task level?

• E.g., automatic/semi-automatic email reply for customer service, literature information service for paper writing (suggest relevant citations, term definitions, etc), comparing prices for shoppers

Page 12: Pick a Good IR Research Problem

2008 © ChengXiang Zhai Dragon Star Lecture at Beijing University, June 21-30, 2008 12

Challenge 3: Support Whole Life Cycle of Information

• A life cycle of information consists of “creation”, “storage”, “transformation”, “consumption”, “recycling”, etc

• Most existing applications support one stage (e.g., search supports “consumption”)

• How can we support the whole life cycle in an integrated way?

• E.g., Community publication/subscription service (no need for crawling, user profiling)

Page 13: Pick a Good IR Research Problem

2008 © ChengXiang Zhai Dragon Star Lecture at Beijing University, June 21-30, 2008 13

Challenge 4: Collaborative Information Management

• Users (especially similar users) often have similar information need

• Users who have explored the information space can share their experiences with other users

• How to exploit the collective expertise of users and allow users to help each other?

• E.g., allowing “information annotation” on the Web (“footprints”), collaborative filtering/retrieval,

Page 14: Pick a Good IR Research Problem

2008 © ChengXiang Zhai Dragon Star Lecture at Beijing University, June 21-30, 2008 14

Optimizing “Research Return”:Pick a Problem Best for You

Your Passion

High (Potential)

Impact

Your Strength

Best problems for you

Find your passion: If you don’t have to work/study for money, what would you do?

Test of impact: If you are given $1M to fund a research project, what would you fund?

Find your strength: If you don’t know your strength, at least avoid your weakness; acquire strength through training

Page 15: Pick a Good IR Research Problem

2008 © ChengXiang Zhai Dragon Star Lecture at Beijing University, June 21-30, 2008 15

Next Lecture :Formulate IR Research Hypothese