Future Trends
                    in
Search User Interfaces




                  Dr. Marti Hearst
                      U...
In some cases,
    blended and                  Primarily search text
    context-sensitive




Fast response time      Se...
Forecasting the Future

   First: What are the larger trends?

            In technology?
              In society?
    Ne...
Wide adoption of touch-
    Latent preferences                 activated devices with
    for audio and video             ...
Trend: Natural Interfaces
What does this mean for Search UIs?

• Longer, more natural queries

• Search that is as social ...
Trend:
More Natural Queries
Trend: Longer, more natural queries

• The research suggests people prefer to state their
  information need rather than u...
A recent example: keywords failed




                                    7
Instead, ask as a question




                             8
And: find an answer




                      9
Advanced user interface design




                                 10
Trend: More Natural Queries

  • Blend two ideas:
    • “sloppy commands”
    • predictions based on user behavior data


...
Sloppy Commands

• Like command languages, but
 • the user has a lot of flexibility in expression
 • so memorization is no...
Sloppy Commands + Visual Feedback

• Can include rich visual feedback
 • Quicksilver in Apple




 • Inky by Miller et al....
Sloppy Commands + Rich Data

• Combine Mozilla’s Ubiquity and Freebase to
  make a flexible predictive query engine
 •   B...
Sloppy Commands + Rich Data

• Combine Mozilla’s Ubiquity and Freebase to
  make a flexible predictive query engine
 •   B...
Far Future Trend: Dialogue

• We’re still far away.
• SIRI is promising as a
  move forward; based on
  state-of-the-art r...
Trend: Social Search

  People are Social; Computers are Lonely.
   Don’t Personalize Search, Socialize it!
Social Search

    Implicit: Suggestions generated as
    a side-effect of search activity.

              Asking: Communi...
Trend: Social Search

• Socially motivated ranking of search results
 • Explicitly recommended
   • Digg, StumbleUpon
   •...
Social Search: Implicit Suggestions
• Human-generated suggestions (augmented
  with statistics) still beat purely machine-...
Social Search: Asking for Answers

 What do people ask of their social networks?
               Type        %             ...
Social Search: Explicit Help via
 Question-Answering Sites

• Content is produced in a manner amenable to
  searching for ...
Social Search:
Seeing info that people you know have seen

• Yahoo MyWeb, Google Social Search




                       ...
Social Search: Explicit Suggestions
 Building Knowledge

• Social knowledge management tools seem promising
• Utilize the ...
Social Search: People Collaborating
Tools to help with this are only just beginning.




Pickens et al., SIGIR 2008       ...
Social Search: People Collaborating
Tools to help with this are only just beginning.




Pickens et al., SIGIR 2008       ...
Future Trend: The Decline of Text

 • Or: the rise of audio/video

 • The “cultural heavy lifting” (in America at
   least...
Future Trend: The Decline of Text
 • Or: the rise of audio/video
   • Video and audio are now easy to produce and share.
 ...
Future Trend:
The Decline of Text and Rise of Audio/Video

• What is currently solved:
  • Ease of creating and sharing vi...
Future Trend:
The Decline of Text and Rise of Audio/Video

• Other advantages
 • Doesn’t require literacy (but can serve a...
Future Trends … not so much?

• Personalization

• Visualization … some breakthroughs are
  needed.




                  ...
Summary

As algorithms get more sophisticated, we can
build search interfaces that allow people to
interact more naturally...
Thank you!



                   Marti Hearst
                      UC Berkeley


  Book full text freely available at:
  ...
The Future of Search (Keynote at I-Know 2010)
The Future of Search (Keynote at I-Know 2010)
The Future of Search (Keynote at I-Know 2010)
The Future of Search (Keynote at I-Know 2010)
The Future of Search (Keynote at I-Know 2010)
The Future of Search (Keynote at I-Know 2010)
The Future of Search (Keynote at I-Know 2010)
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The Future of Search (Keynote at I-Know 2010)

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I made this talk in response to an invitation to give the opening keynote on the topic of the future of search interfaces at the i-Know conference in Graz, Austria, in Sept 2010: http://i-know.tugraz.at/

Published in: Technology

The Future of Search (Keynote at I-Know 2010)

  1. 1. Future Trends in Search User Interfaces Dr. Marti Hearst UC Berkeley i-Know Conference Keynote Sept 1, 2010
  2. 2. In some cases, blended and Primarily search text context-sensitive Fast response time Search Support for related queries Interfaces and documents today? Navigation and Tailored to keyword organization queries and iterating support from on the information faceted metadata 3
  3. 3. Forecasting the Future First: What are the larger trends? In technology? In society? Next: Project out from these.
  4. 4. Wide adoption of touch- Latent preferences activated devices with for audio and video excellent UI design Wide adoption of social media and user-generated Increasingly Natural available rich, integrated data Interfaces sources Improvements in Wide adoption of NLP, speech mobile devices with recognition via huge data sets 3
  5. 5. Trend: Natural Interfaces What does this mean for Search UIs? • Longer, more natural queries • Search that is as social as people are • Deep integration of audio and video • Dialogue and conversational (farther out) 4
  6. 6. Trend: More Natural Queries
  7. 7. Trend: Longer, more natural queries • The research suggests people prefer to state their information need rather than use keywords. • But after first using a search engine they quickly learned that full questions resulted in failure. • Average query length continues to increase • Major search engines are now handling long queries well. • Information worded as questions is increasing on the web. • From social question-answering sites and forums. 6
  8. 8. A recent example: keywords failed 7
  9. 9. Instead, ask as a question 8
  10. 10. And: find an answer 9
  11. 11. Advanced user interface design 10
  12. 12. Trend: More Natural Queries • Blend two ideas: • “sloppy commands” • predictions based on user behavior data • This behavior is subtly and steadily increasing in sophistication across many interfaces. 11
  13. 13. Sloppy Commands • Like command languages, but • the user has a lot of flexibility in expression • so memorization is not required • “time graz” “what time is it in graz” “graz time now” 12
  14. 14. Sloppy Commands + Visual Feedback • Can include rich visual feedback • Quicksilver in Apple • Inky by Miller et al. 13
  15. 15. Sloppy Commands + Rich Data • Combine Mozilla’s Ubiquity and Freebase to make a flexible predictive query engine • By spencerwaterbed: http://vimeo.com/13992710 14
  16. 16. Sloppy Commands + Rich Data • Combine Mozilla’s Ubiquity and Freebase to make a flexible predictive query engine • By spencerwaterbed: http://vimeo.com/13992710 15
  17. 17. Far Future Trend: Dialogue • We’re still far away. • SIRI is promising as a move forward; based on state-of-the-art research. 16
  18. 18. Trend: Social Search People are Social; Computers are Lonely. Don’t Personalize Search, Socialize it!
  19. 19. Social Search Implicit: Suggestions generated as a side-effect of search activity. Asking: Communicating directly with others. Explicit: knowledge accumulating via the deliberate contributions of many. Collaborative: Working with other people on a search task. 18
  20. 20. Trend: Social Search • Socially motivated ranking of search results • Explicitly recommended • Digg, StumbleUpon • Delicious, Furl • Google’s SearchWiki • Implicitly recommended • Click-through • People who bought… • Yahoo’s MyWeb (now Google Social Search) 19
  21. 21. Social Search: Implicit Suggestions • Human-generated suggestions (augmented with statistics) still beat purely machine- generated ones. • Spelling suggestions • Query term suggestions (“search as you type”) • Recommendations (books, movies, etc) • Ranking (using clickthrough statistics) 20
  22. 22. Social Search: Asking for Answers What do people ask of their social networks? Type % Example Building a new playlist – any ideas for good running songs? Recommendation 29% I am wondering if I should buy the Kitchen-Aid ice cream maker? Opinion 22% Anyone know a way to put Excel charts into LaTeX? Factual 17% Rhetorical 14% Why are men so stupid? Invitation 9% Who wants to go to Navya Lounge this evening? Need a babysitter in a big way tonight… anyone?? Favor 4% I am hiring in my team. Do you know anyone who would be interested? Social connection 3% Offer 1% Could any of my friends use boys size 4 jeans? Morris et al., CHI 2010 21
  23. 23. Social Search: Explicit Help via Question-Answering Sites • Content is produced in a manner amenable to searching for answers to questions. • Search tends to work well on these sites and on the internet leading to these sites • Like an FAQ but • with many authors, and • with the questions that the audience really wants the answers to, and • written in the language the audience wants to use. 22
  24. 24. Social Search: Seeing info that people you know have seen • Yahoo MyWeb, Google Social Search 23
  25. 25. Social Search: Explicit Suggestions Building Knowledge • Social knowledge management tools seem promising • Utilize the best of social networks, tagging, blogging, web page creation, wikis, and search. Millen et al., CHI 2006 24
  26. 26. Social Search: People Collaborating Tools to help with this are only just beginning. Pickens et al., SIGIR 2008 25
  27. 27. Social Search: People Collaborating Tools to help with this are only just beginning. Pickens et al., SIGIR 2008 25
  28. 28. Future Trend: The Decline of Text • Or: the rise of audio/video • The “cultural heavy lifting” (in America at least)is moving from text to audio and video. (Full essay at http://edge.org/q2009/q09_9.html#hearst) 26
  29. 29. Future Trend: The Decline of Text • Or: the rise of audio/video • Video and audio are now easy to produce and share. • Pew: Use of video sharing sites doubled from 2006-2009 • YouTube: Video “responses” apparently arose spontaneously • Videos for presidential debates were mundane. • Millions of video views; no where near this number for article readings • Pew: Marketing emails with podcasts 20% more likely to be opened. • Movies with subtitles do poorly in the U.S. • Newspaper web sites are starting to look like TV. (Full essay at http://edge.org/q2009/q09_9.html#hearst) 26
  30. 30. Future Trend: The Decline of Text and Rise of Audio/Video • What is currently solved: • Ease of creating and sharing videos • What needs improvement: • Editing tools • The main impediments to more fully replacing text are: • The need for better search and scanning of audio and video • A means for silent audio input • What about the popularity of texting? • An interesting counter-trend • Especially popular among youth • Cheap • Can be done surreptitiously (Full essay at http://edge.org/q2009/q09_9.html#hearst) 28
  31. 31. Future Trend: The Decline of Text and Rise of Audio/Video • Other advantages • Doesn’t require literacy (but can serve as a bridge) • Robust video devices to teach agricultural techniques • What about the popularity of texting? • An interesting counter-trend • Especially popular among youth • Cheap • Can be done surreptitiously (Full essay at http://edge.org/q2009/q09_9.html#hearst) 27
  32. 32. Future Trends … not so much? • Personalization • Visualization … some breakthroughs are needed. 29
  33. 33. Summary As algorithms get more sophisticated, we can build search interfaces that allow people to interact more naturally: • More language-like queries • Speaking & hearing rather than typing & reading • Interacting with other people while doing search tasks • Leveraging the knowledge in peoples’ heads. 30
  34. 34. Thank you! Marti Hearst UC Berkeley Book full text freely available at: http://searchuserinterfaces.com

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