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The Resource Human computation, Edith Law and Luis von Ahn, (electronic book)

Human computation, Edith Law and Luis von Ahn, (electronic book)

Label
Human computation
Title
Human computation
Statement of responsibility
Edith Law and Luis von Ahn
Creator
Contributor
Subject
Language
eng
Summary
Human computation is a new and evolving research area that centers around harnessing human intelligence to solve computational problems that are beyond the scope of existing Artificial Intelligence (AI) algorithms. With the growth of the Web, human computation systems can now leverage the abilities of an unprecedented number of people via the Web to perform complex computation.There are various genres of human computation applications that exist today. Games with a purpose (e.g., the ESP Game) specifically target online gamers who generate useful data (e.g., image tags) while playing an enjoyable game. Crowdsourcing marketplaces (e.g., Amazon Mechanical Turk) are human computation systems that coordinate workers to perform tasks in exchange for monetary rewards. In identity verification tasks, users perform computation in order to gain access to some online content; an example is reCAPTCHA, which leverages millions of users who solve CAPTCHAs every day to correct words in books that optical character recognition (OCR) programs fail to recognize with certainty. This book is aimed at achieving four goals: (1) defining human computation as a research area; (2) providing a comprehensive review of existing work; (3) drawing connections to a wide variety of disciplines, including AI, Machine Learning, HCI, Mechanism/Market Design and Psychology, and capturing their unique perspectives on the core research questions in human computation; and (4) suggesting promising research directions for the future
Member of
Cataloging source
CaBNVSL
http://library.link/vocab/creatorName
Law, Edith
Dewey number
001.532
Illustrations
illustrations
Index
no index present
LC call number
Q320
LC item number
.L284 2011
Literary form
non fiction
Nature of contents
  • dictionaries
  • abstracts summaries
  • bibliography
http://library.link/vocab/relatedWorkOrContributorName
Ahn, Luis von
http://library.link/vocab/subjectName
  • Bionics
  • Human-computer interaction
  • Machine learning
  • Artificial intelligence
  • Social media
Target audience
  • adult
  • specialized
Label
Human computation, Edith Law and Luis von Ahn, (electronic book)
Instantiates
Publication
Bibliography note
Includes bibliographical references (p. 77-103)
Color
multicolored
Contents
  • Preface -- Acknowledgments --
  • 1. Introduction -- 1.1 Computation: now and then -- 1.2 What is human computation? -- 1.2.1 Explicit control -- 1.3 Tackling AI problems: from vision to biology -- 1.3.1 A matter of perception -- 1.3.2 The language barrier -- 1.3.3 Intuition into computationally intensive problems -- 1.4 Overview --
  • Part I. Solving computational problems -- 2. Human computation algorithms -- 2.1 A definition of algorithms -- 2.2 Building blocks of algorithms -- 2.2.1 Operations, controls and program synthesis -- 2.3 Programming frameworks -- 2.4 Evaluating human computation algorithms -- 2.4.1 Correctness -- 2.4.2 Efficiency -- 2.5 Summary --
  • 3. Aggregating outputs -- 3.1 Objective versus cultural truth -- 3.2 Classification -- 3.2.1 Latent class models -- 3.2.2 Learning from imperfect data -- 3.3 Beyond classification -- 3.3.1 Ranking and voting -- 3.3.2 Clustering -- 3.3.3 Structured outputs -- 3.3.4 Beliefs -- 3.4 Summary --
  • 4. Task routing -- 4.1 Push versus pull approaches -- 4.2 Push approach -- 4.2.1 Allocation -- 4.2.2 Matching -- 4.2.3 Inference -- 4.3 Pull approacH -- 4.3.1 Search and visualization -- 4.3.2 Task recommendation -- 4.3.3 Peer routing -- 4.4 Evaluation criteria -- 4.5 Summary --
  • Part II. Design -- 5. Understanding workers and requesters -- 5.1 Markets -- 5.1.1 Mechanical Turk and paid crowdsourcing -- 5.1.2 Security and access -- 5.1.3 Gamers -- 5.1.4 Citizen science -- 5.1.5 Learners -- 5.1.6 Temporary markets -- 5.2 Supporting end users -- 5.2.1 Workers -- 5.2.2 Requesters -- 5.3 Summary --
  • 6. The art of asking questions -- 6.1 Designing tasks -- 6.1.1 Information -- 6.1.2 Granularity -- 6.1.3 Independence -- 6.1.4 Incentives -- 6.1.5 Quality control -- 6.2 Eliciting truthful responses -- 6.2.1 Human computation games -- 6.2.2 Leveraging communication -- 6.2.3 Explicitly preventing bad outputs -- 6.2.4 A brief survey of games and mechanisms -- 6.3 Summary -- Part III. Conclusion --
  • 7. The future of human computation -- 7.1 Research directions -- 7.1.1 Interweaving human and machine intelligence -- 7.1.2 Fostering long-term relationships -- 7.1.3 Designing organizations and task markets -- 7.2 Conclusion --
  • Bibliography -- Authors' biographies
Control code
201107AIM013
Dimensions
unknown
Extent
1 electronic text (xi, 105 p.)
File format
multiple file formats
Form of item
online
Isbn
9781608455171
Issn
1939-4616
Other physical details
ill., digital file.
Reformatting quality
access
Specific material designation
remote
Label
Human computation, Edith Law and Luis von Ahn, (electronic book)
Publication
Bibliography note
Includes bibliographical references (p. 77-103)
Color
multicolored
Contents
  • Preface -- Acknowledgments --
  • 1. Introduction -- 1.1 Computation: now and then -- 1.2 What is human computation? -- 1.2.1 Explicit control -- 1.3 Tackling AI problems: from vision to biology -- 1.3.1 A matter of perception -- 1.3.2 The language barrier -- 1.3.3 Intuition into computationally intensive problems -- 1.4 Overview --
  • Part I. Solving computational problems -- 2. Human computation algorithms -- 2.1 A definition of algorithms -- 2.2 Building blocks of algorithms -- 2.2.1 Operations, controls and program synthesis -- 2.3 Programming frameworks -- 2.4 Evaluating human computation algorithms -- 2.4.1 Correctness -- 2.4.2 Efficiency -- 2.5 Summary --
  • 3. Aggregating outputs -- 3.1 Objective versus cultural truth -- 3.2 Classification -- 3.2.1 Latent class models -- 3.2.2 Learning from imperfect data -- 3.3 Beyond classification -- 3.3.1 Ranking and voting -- 3.3.2 Clustering -- 3.3.3 Structured outputs -- 3.3.4 Beliefs -- 3.4 Summary --
  • 4. Task routing -- 4.1 Push versus pull approaches -- 4.2 Push approach -- 4.2.1 Allocation -- 4.2.2 Matching -- 4.2.3 Inference -- 4.3 Pull approacH -- 4.3.1 Search and visualization -- 4.3.2 Task recommendation -- 4.3.3 Peer routing -- 4.4 Evaluation criteria -- 4.5 Summary --
  • Part II. Design -- 5. Understanding workers and requesters -- 5.1 Markets -- 5.1.1 Mechanical Turk and paid crowdsourcing -- 5.1.2 Security and access -- 5.1.3 Gamers -- 5.1.4 Citizen science -- 5.1.5 Learners -- 5.1.6 Temporary markets -- 5.2 Supporting end users -- 5.2.1 Workers -- 5.2.2 Requesters -- 5.3 Summary --
  • 6. The art of asking questions -- 6.1 Designing tasks -- 6.1.1 Information -- 6.1.2 Granularity -- 6.1.3 Independence -- 6.1.4 Incentives -- 6.1.5 Quality control -- 6.2 Eliciting truthful responses -- 6.2.1 Human computation games -- 6.2.2 Leveraging communication -- 6.2.3 Explicitly preventing bad outputs -- 6.2.4 A brief survey of games and mechanisms -- 6.3 Summary -- Part III. Conclusion --
  • 7. The future of human computation -- 7.1 Research directions -- 7.1.1 Interweaving human and machine intelligence -- 7.1.2 Fostering long-term relationships -- 7.1.3 Designing organizations and task markets -- 7.2 Conclusion --
  • Bibliography -- Authors' biographies
Control code
201107AIM013
Dimensions
unknown
Extent
1 electronic text (xi, 105 p.)
File format
multiple file formats
Form of item
online
Isbn
9781608455171
Issn
1939-4616
Other physical details
ill., digital file.
Reformatting quality
access
Specific material designation
remote

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