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The Future of Search
jrowley@uchicago.edu & danya@uchicago.edu
Organizing Principles
Challenges
2 Potential Ways Forward:
...
Organizing Principles
• Reduction of Interactional Friction
• Connecting Intent with Action
“Flights from Chicago to NY” “UChicago to Billy Sunday”
The Billy Sunday Problem
• Simply searching for “Billy
Sunday” returns a mess of
results
• Google returns what it “thinks”...
The problem with strings
• String-based search is old.
• Results in increased
interactional friction
More Problems with String-
based Search
• The previous approach leaves
users with two choices:
• Parse the hodgepodge
• Ap...
Things > Strings
• Across web platforms, we’ve
seen a paradigm shift from
“string thinking” to graph-
based approach
• See...
Unpacking Google’s
Knowledge Graph
• Google’s attempt to structure
its data the way humans
structure knowledge
internally....
Back to Billy Sunday
• Again, the string-based
search approach yields messy
results
• “Billy Sunday” belongs to
many diffe...
Attacking the Context Problem
• Google is attempting to address this context
problem with the semantic Knowledge Graph
• T...
Search in a multiplatform
ecosystem
• The arrival of third, fourth and
fifth screens raises a number
of questions about th...
Search as Background
Process
• Search is morphing from an
active behavior to a passive
one
• Relevant information is
repre...
Structured Data
• Search engines use metadata
to interpret data and give
users relevant results
• We’ve already seen some
...
Delivering on Ambient
Location Awareness
• Passive streaming of your
location helps search engines
better infer intent
• S...
Microsoft Cortana Google Now
Search as Conversation with
Future AI Systems
• The chat window may replace
the search bar
• Friendly voices may replace
g...
Discussion Questions
• What are the major defining features of the Knowledge Graph Optimization
described in this presenta...
The Future of Search
The Future of Search
The Future of Search
The Future of Search
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The Future of Search

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View notes here: http://www.slideshare.net/JasonDonaldRowley/notes-on-46898401

This presentation was prepared for a 5-minute O'Reilly Ignite-style talk delivered for Professor James Evans's Internet and Society course at the University of Chicago. It details the current search landscape, some of the challenges facing incumbents like Google, and some of the products innovating on the core search experience.

Published in: Internet
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The Future of Search

  1. 1. The Future of Search jrowley@uchicago.edu & danya@uchicago.edu Organizing Principles Challenges 2 Potential Ways Forward: - Google’s Knowledge Graph - Microsoft Cortana & Google Now
  2. 2. Organizing Principles • Reduction of Interactional Friction • Connecting Intent with Action
  3. 3. “Flights from Chicago to NY” “UChicago to Billy Sunday”
  4. 4. The Billy Sunday Problem • Simply searching for “Billy Sunday” returns a mess of results • Google returns what it “thinks” is most relevant to me, even if the content isn’t relevant to me • This is illustrative of a bigger point
  5. 5. The problem with strings • String-based search is old. • Results in increased interactional friction
  6. 6. More Problems with String- based Search • The previous approach leaves users with two choices: • Parse the hodgepodge • Append the query with modifying terms • Both choices increase interactional friction == bad UX
  7. 7. Things > Strings • Across web platforms, we’ve seen a paradigm shift from “string thinking” to graph- based approach • See, for example: Facebook’s Social Graph & OGP, Google’s Knowledge Graph, LinkedIn’s Professional Graph, Wolfram’s Computational Knowledge Engine, &c.
  8. 8. Unpacking Google’s Knowledge Graph • Google’s attempt to structure its data the way humans structure knowledge internally. • Humans interpret the world in terms of things, not strings • The Knowledge Graph is a more “humane” way of interfacing with information
  9. 9. Back to Billy Sunday • Again, the string-based search approach yields messy results • “Billy Sunday” belongs to many different concepts • Ex. Billy Sunday is in the set of “Swanky Chicago Cocktail Bars”, the set of “Temperance Preachers” and “Professional Baseball Players”
  10. 10. Attacking the Context Problem • Google is attempting to address this context problem with the semantic Knowledge Graph • The Knowledge Graph is a growing, morphing database that can measure relationships between entities in 100-dimensional space • This is the core of Google’s search strategy going forward
  11. 11. Search in a multiplatform ecosystem • The arrival of third, fourth and fifth screens raises a number of questions about the future of search. • People behave differently on mobile devices • Desktop search UX does not map well onto small screens
  12. 12. Search as Background Process • Search is morphing from an active behavior to a passive one • Relevant information is represented in new ways and delivered through novel channels
  13. 13. Structured Data • Search engines use metadata to interpret data and give users relevant results • We’ve already seen some examples of structured data at work in search results • Some platforms (like Facebook and Wolfram|Alpha) are more structured than others
  14. 14. Delivering on Ambient Location Awareness • Passive streaming of your location helps search engines better infer intent • Some search engines use location data to trigger information discovery events for the user
  15. 15. Microsoft Cortana Google Now
  16. 16. Search as Conversation with Future AI Systems • The chat window may replace the search bar • Friendly voices may replace graphical user interface on keyboard-free devices • We already see this happening with “AI” services like DigitalGenius • And human-powered ones like Magic
  17. 17. Discussion Questions • What are the major defining features of the Knowledge Graph Optimization described in this presentation, and how do they relate to previous attempts to organize information that we have covered in the lecture and the readings? • How does the structure of information influence the user’s process of gathering information? How does it effect the production of future knowledge, and/or human action? Is someone searching for Billy Sunday who finds a different result than they were looking for likely to change their mind or behavior? • To what extent is search determined by structure, and to what extent is it determined by user? • Is “friction” entirely bad in search? Do we lose anything when we automate the suggestion process instead of leaving room for surprise?

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