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A novel trilling operator for DBMSs
     (and other sw systems)




                     Paolo Merialdo (Uniroma3)
A novel trilling operator for DBMSs
         (and other sw systems)

          Houyhnhnms*        (pron. ˈhwi-məm)




* Thanks to Jonathan Swift
A novel trilling operator for DBMSs
         (and other sw systems)

          Houyhnhnms*
                         (pron. ˈhwi-məm)


* Thanks to Jonathan Swift
An Amazon issue…
Categorize products with 1.0 accuracy

Unfeasible without introducing human
     intelligence in the pipeline
An Amazon issue…
…became a market opportunity!



Mechanical Turk!
An Amazon issue…
…became a market opportunity!

       Mechanical Turk
Amazon Mechanical Turk
A marketplace for HITs (Human Intelligent Tasks)

"Requesters" (employers) post tasks

"Workers" (on line users) pickup and complete
task

Payment (few cents for HIT)
Typical (frequently posted) Tasks
   Transcription
   Content generation
   Content rewriting
   Object classification
   Content evaluation and feedback
   Mediator for other requesters (!)



Panagiotis Ipeirotis (NYU) "Analyzing the Amazon Mechanical Turk Marketplace"
90% of HITS < $0.10
                                    Prices*




* Data collected from January 2009 till April 2010
Panagiotis Ipeirotis (NYU) "Analyzing the Amazon Mechanical Turk Marketplace"
Volume of transactions
 90% of days < $2,000




   median arrival rate: $1,040 per day
   median completion rate: $1,155 per day


* Data collected from January 2009 till April 2010
Panagiotis Ipeirotis (NYU) "Analyzing the Amazon Mechanical Turk Marketplace"
Responsiveness and reward




        Assignment: 100 HITs


Michael Franklin et al (Berkeley and ETH) CrowdDB: Answering Queries with Crowdsourcing
Not only AMT

   RABJ (FreeBase)
            2.3M human judgments
            18 sec/judgment
            Tipical Tasks: reconciliations, typeWriter,
                  geographers, genderizer



Shailesh Kochhar et al "The Anatomy of a large scale human computation engine"
Not only AMT

SamaSource
 founder Leila Chirayath Janah (26)
 social business (raised > 5M$ from Google,
    Rockefeller, Ford Foundation et al)
 >2,000 worker from dev. countries (India, Kenya)
 15$ day per worker
 To date paid out 1M$ in wages
Not only AMT
Startups!
      Crowdflowers
           (organize AMT HITS for enterprises)
      uTest: sw testing
           (functional, UX, usability)
      MicroTask: doc processing
           (feed paper docs into systems)
Houyhnhnms are among us…
Michael Franklin et al (Berkeley and ETH) CrowdDB: Answering Queries with Crowdsourcing
Michael Franklin et al (Berkeley and ETH) CrowdDB: Answering Queries with Crowdsourcing
References
•   https://www.mturk.com/
•   http://samasource.org/
•   http://www.utest.com/
•   http://crowdflower.com/
•   http://www.microtask.com/
References
• Michael Franklin et al (Berkeley and ETH)
  CrowdDB: Answering Queries with Crowdsourcing
• Shailesh Kochhar et al (Metaweb Tech)
  "The Anatomy of a large scale human computation engine"
• Panagiotis Ipeirotis (NYU)
  "Analyzing the Amazon Mechanical Turk Marketplace"
• Aditya Parameswaran et al (Stanford U)
  "Answering Queries using Humans, Algorithms and Databases"
• http://amplab.cs.berkeley.edu/
• Adam Marcus et Al (MIT)
  Crowdsourced Databases: Query Processing with People

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Codemotion2012

  • 1. A novel trilling operator for DBMSs (and other sw systems) Paolo Merialdo (Uniroma3)
  • 2. A novel trilling operator for DBMSs (and other sw systems) Houyhnhnms* (pron. ˈhwi-məm) * Thanks to Jonathan Swift
  • 3. A novel trilling operator for DBMSs (and other sw systems) Houyhnhnms* (pron. ˈhwi-məm) * Thanks to Jonathan Swift
  • 4. An Amazon issue… Categorize products with 1.0 accuracy Unfeasible without introducing human intelligence in the pipeline
  • 5. An Amazon issue… …became a market opportunity! Mechanical Turk!
  • 6. An Amazon issue… …became a market opportunity! Mechanical Turk
  • 7. Amazon Mechanical Turk A marketplace for HITs (Human Intelligent Tasks) "Requesters" (employers) post tasks "Workers" (on line users) pickup and complete task Payment (few cents for HIT)
  • 8. Typical (frequently posted) Tasks Transcription Content generation Content rewriting Object classification Content evaluation and feedback Mediator for other requesters (!) Panagiotis Ipeirotis (NYU) "Analyzing the Amazon Mechanical Turk Marketplace"
  • 9. 90% of HITS < $0.10 Prices* * Data collected from January 2009 till April 2010 Panagiotis Ipeirotis (NYU) "Analyzing the Amazon Mechanical Turk Marketplace"
  • 10. Volume of transactions 90% of days < $2,000 median arrival rate: $1,040 per day median completion rate: $1,155 per day * Data collected from January 2009 till April 2010 Panagiotis Ipeirotis (NYU) "Analyzing the Amazon Mechanical Turk Marketplace"
  • 11. Responsiveness and reward Assignment: 100 HITs Michael Franklin et al (Berkeley and ETH) CrowdDB: Answering Queries with Crowdsourcing
  • 12. Not only AMT RABJ (FreeBase) 2.3M human judgments 18 sec/judgment Tipical Tasks: reconciliations, typeWriter, geographers, genderizer Shailesh Kochhar et al "The Anatomy of a large scale human computation engine"
  • 13. Not only AMT SamaSource founder Leila Chirayath Janah (26) social business (raised > 5M$ from Google, Rockefeller, Ford Foundation et al) >2,000 worker from dev. countries (India, Kenya) 15$ day per worker To date paid out 1M$ in wages
  • 14. Not only AMT Startups! Crowdflowers (organize AMT HITS for enterprises) uTest: sw testing (functional, UX, usability) MicroTask: doc processing (feed paper docs into systems)
  • 16. Michael Franklin et al (Berkeley and ETH) CrowdDB: Answering Queries with Crowdsourcing
  • 17. Michael Franklin et al (Berkeley and ETH) CrowdDB: Answering Queries with Crowdsourcing
  • 18. References • https://www.mturk.com/ • http://samasource.org/ • http://www.utest.com/ • http://crowdflower.com/ • http://www.microtask.com/
  • 19. References • Michael Franklin et al (Berkeley and ETH) CrowdDB: Answering Queries with Crowdsourcing • Shailesh Kochhar et al (Metaweb Tech) "The Anatomy of a large scale human computation engine" • Panagiotis Ipeirotis (NYU) "Analyzing the Amazon Mechanical Turk Marketplace" • Aditya Parameswaran et al (Stanford U) "Answering Queries using Humans, Algorithms and Databases" • http://amplab.cs.berkeley.edu/ • Adam Marcus et Al (MIT) Crowdsourced Databases: Query Processing with People