design for interaction
Daniel Tunkelang
Chief Scientist, Endeca
© 2009 Endeca Technologies, Inc. All rights reserved.

about me
Organizing SIGIR ’09 Industry Track in Boston on July 22nd!
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about endeca
leading provider of
search applications
250M+
end users
per month
600+ customers
$100M+ annual sales
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what i hope you learn from this talk
the db and ir perspectives have a common thread
convergence may be upon us
but we need interaction to make it work
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overview
don't put all your eggs in one basket
design for interaction
human-computer information retrieval
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don’t put all your eggs in one basket
Still Life with Basket and Broken Eggs by Michael Edwards, 2008
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the db approach: perfection in, perfection out
http://www.storeitfoodsblog.com/category/food-preparation/meat-grinder/
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db usability researchers recognize the pain
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sql is hard
Making Database Systems Usable
[Jagadish et al., SIGMOD 2007]
__
sql
• labor-intensive query construction
• lengthy query evaluation
• high query reformulation cost
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data sucks and users are lazy
Extracting Problems for Database
and IR Researchers
[Naughton, Spring 2008 North East DB/IR Day]
• real data is
– incomplete
– inconsistent
– incorrect
• users don’t want to learn
– data schemas
– structured query languages we’re not gonna take it!
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the ir way: don’t worry, be happy
http://adsoftheworld.com/media/print/mcdonalds_burger_mysteries
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ir for db people: what would google do?
tf-idf PageRank
SYSTEM:
rank using IR model
USER:
information Need query select from results
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assumptions of relevance-centric ir approach
• self-awareness
• self-expression
• model knows best
• answer is a document
• one-shot query
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life is not a batch
• db approach expects too much of user
• ir approach expects too much of system
both approaches act as if it all
comes down to a single query
is that your final answer question?
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design for interaction
The Future of Social Interaction by Jim Stoten
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changes assumptions about what to optimize
precision
recall
complexity relevance
communication
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how do we optimize communication?
transparency
guidance
control
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ir offers a black box
ca c'est la caisse. le mouton que tu veux est dedans.
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db / set retrieval offers 2 out of 3
transparency
guidance
control
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but we need it all!
• set retrieval is a failure in the ir world
– though quite successful in the db world!
• but ranked retrieval is inherently crippled
– no transparency, control, or guidance!
how do we optimize for communication?
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human-computer information retrieval
“Toward Human-Computer
Information Retrieval”
Gary Marchionini
• don’t just guess the user’s intent
• increase user responsibility and control
• require and reward human intellectual effort
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great idea
how?
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treat query construction as a process
A Case for Interaction
[Koenemann and Belkin, 1996]
• used term feedback to improve alerting queries
• users select from suggested terms
• 17 – 34% improvement in precision @ 30
• users liked the feedback interface
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expose the facets of semistructured content
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success in the lab and the field
• favored in user studies by Marti Hearst
– http://flamenco.berkeley.edu/
• ubiquitous in ecommerce
– amazon.com
– eBay
– endeca powers 42 of top 100 online retailers
• taking over media, libraries, enterprise, etc.
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even a few db folks have drunk the kool-aid
DataGuides
[Goldman and Widom, VLDB 1997]
• user-friendly schema summaries
Magnet
[Sinha and Karger, SIGMOD 2005]
• navigation and refinement options
common theme: semistructured
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what is semistructured data?
• one universe
• self-describing
• blends data / meta-data
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data modeling flexibility
• no a-priori schema
– integrated sources without up-front schema design
• richer modeling capabilities tame data complexity
– hierarchy, multi-valued fields, sparse fields
• schema flexibility eases schema evolution
– new entity types, new data source
WWW SOA, ESB, Groupware and Content
Databases ERP
Internet File Systems Web Service Collaboration Management
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semantically direct queries
which attributes
which on-sale items characterize on-sale
are available in blue? blue items?
price, sleeve,
color, salePrice,
brand, fabric, …
<shirt>
<buyingGuide>
<sku>1234</sku>
<title>Selecting the right
<sleeve>Long</sleeve>
ski coat for you.</title>
<desc>Classic end-on-end shirt</desc>
<file>skiguide.pdf</file>
<price>39.99</price>
<keyword>ski</keyword>
<salePrice>29.99</salePrice>
<keyword>coat</keyword>
<color>Blue</color>
...
<color>Yellow</color>
</buyingGuide>
<color>White</color>
...
</shirt> <trousers>
<sku>1579</sku>
<price>59.99</price>
<color>Khaki</color>
...
</trousers>
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but let’s make this concrete
Uh oh, I’m presenting at
SIGMOD! Better find a good
book about databases!
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quick, to the goog-mobile!
not quite…
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i know, i’ll go to the library!
#%@$!
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let’s try a little hcir…
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hcir works for news too
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life in a semistructured world
• search is a great starting point
– users can’t / won’t initiate structured queries
• ranked lists are an inadequate ending point
– search queries are lossy projections of intent
• hcir leads users down a garden path to structure
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lots of trade-offs
“everything should be made as simple
as possible, but no simpler”
“speed of thought” vs. “going nowhere quickly”
“to err is human, but to really foul
things up requires a computer”
simple interfaces don’t
always yield satisfaction
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users want the triumvirate
• transparency
• control
• guidance
transparency and control are easy
guidance requires cleverness
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in closing
all of us want to help people access information
the best help is to help them help themselves
design for interaction though
transparency, control, guidance
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thank you…and come to SIGIR!
communication 1.0
email: dt@endeca.com
communication 2.0
blog: http://thenoisychannel.com
twitter: http://twitter.com/dtunkelang
SIGIR: July 19-23 in Boston
Industry Track on July 22nd!
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