Crowdsourced data management : hybrid machine-human computing /: hybrid machine-human computing. (2018)
- Record Type:
- Book
- Title:
- Crowdsourced data management : hybrid machine-human computing /: hybrid machine-human computing. (2018)
- Main Title:
- Crowdsourced data management : hybrid machine-human computing
- Further Information:
- Note: Guoliang Li, Jiannan Wang, Yudian Zheng, Ju Fan, Michael J. Franklin.
- Authors:
- Li, Guoliang
Wang, Harry (Harry Jiannan)
Zheng, Yudian
Fan, Ju
Franklin, Michael J - Contents:
- Intro; Preface; Acknowledgments; Contents; 1 Introduction; 1.1 Motivation; 1.2 Crowdsourcing Overview; 1.3 Crowdsourced Data Management; References; 2 Crowdsourcing Background; 2.1 Crowdsourcing Overview; 2.2 Crowdsourcing Workflow; 2.2.1 Workflow from Requester Side; 2.2.1.1 Task Design; 2.2.1.2 Task Settings; 2.2.1.3 Task Deployment; 2.2.2 Workflow from Worker Side; 2.2.3 Workflow from Platform Side; 2.3 Crowdsourcing Platforms; 2.3.1 Amazon Mechanical Turk (AMT); 2.3.2 CrowdFlower; 2.3.3 Other Platforms; 2.4 Existing Surveys, Tutorials, and Books 2.5 Optimization Goal of Crowdsourced Data ManagementReferences; 3 Quality Control; 3.1 Overview of Quality Control; 3.2 Truth Inference; 3.2.1 Truth Inference Problem; 3.2.2 Unified Solution Framework; 3.2.3 Comparisons of Existing Works; 3.2.3.1 Task Modeling; 3.2.3.2 Worker Modeling; 3.2.3.3 Applied Techniques; 3.2.4 Extensions of Truth Inference; 3.3 Task Assignment; 3.3.1 Task Assignment Setting; 3.3.1.1 Answer Uncertainty; 3.3.1.2 Worker Quality; 3.3.1.3 Objectives of Requesters; 3.3.2 Worker Selection Setting; 3.4 Summary of Quality Control; References; 4 Cost Control 4.1 Overview of Cost Control4.2 Task Pruning; 4.2.1 Difficulty Measurement; 4.2.2 Threshold Selection; 4.2.3 Pros and Cons; 4.3 Answer Deduction; 4.3.1 Iterative Workflow; 4.3.2 Presentation Order; 4.3.3 Pros and Cons; 4.4 Task Selection; 4.4.1 Model-Driven; 4.4.2 Problem-Driven; 4.4.3 Pros and Cons; 4.5 Sampling; 4.5.1 Crowdsourced Aggregation; 4.5.2 DataIntro; Preface; Acknowledgments; Contents; 1 Introduction; 1.1 Motivation; 1.2 Crowdsourcing Overview; 1.3 Crowdsourced Data Management; References; 2 Crowdsourcing Background; 2.1 Crowdsourcing Overview; 2.2 Crowdsourcing Workflow; 2.2.1 Workflow from Requester Side; 2.2.1.1 Task Design; 2.2.1.2 Task Settings; 2.2.1.3 Task Deployment; 2.2.2 Workflow from Worker Side; 2.2.3 Workflow from Platform Side; 2.3 Crowdsourcing Platforms; 2.3.1 Amazon Mechanical Turk (AMT); 2.3.2 CrowdFlower; 2.3.3 Other Platforms; 2.4 Existing Surveys, Tutorials, and Books 2.5 Optimization Goal of Crowdsourced Data ManagementReferences; 3 Quality Control; 3.1 Overview of Quality Control; 3.2 Truth Inference; 3.2.1 Truth Inference Problem; 3.2.2 Unified Solution Framework; 3.2.3 Comparisons of Existing Works; 3.2.3.1 Task Modeling; 3.2.3.2 Worker Modeling; 3.2.3.3 Applied Techniques; 3.2.4 Extensions of Truth Inference; 3.3 Task Assignment; 3.3.1 Task Assignment Setting; 3.3.1.1 Answer Uncertainty; 3.3.1.2 Worker Quality; 3.3.1.3 Objectives of Requesters; 3.3.2 Worker Selection Setting; 3.4 Summary of Quality Control; References; 4 Cost Control 4.1 Overview of Cost Control4.2 Task Pruning; 4.2.1 Difficulty Measurement; 4.2.2 Threshold Selection; 4.2.3 Pros and Cons; 4.3 Answer Deduction; 4.3.1 Iterative Workflow; 4.3.2 Presentation Order; 4.3.3 Pros and Cons; 4.4 Task Selection; 4.4.1 Model-Driven; 4.4.2 Problem-Driven; 4.4.3 Pros and Cons; 4.5 Sampling; 4.5.1 Crowdsourced Aggregation; 4.5.2 Data Cleaning; 4.5.3 Pros and Cons; 4.6 Task Design; 4.6.1 User Interface Design; 4.6.2 Non-monetary Incentives; 4.6.3 Pros and Cons; 4.7 Summary of Cost Control; References; 5 Latency Control; 5.1 Overview of Latency Control 5.2 Single-Task Latency Control5.2.1 Recruitment Time; 5.2.2 Qualification Test Time; 5.2.3 Work Time; 5.3 Single-Batch Latency Control; 5.3.1 Statistical Model; 5.3.2 Straggler Mitigation; 5.4 Multi-batch Latency Control; 5.4.1 Motivation of Multiple Batches; 5.4.2 Two Basic Ideas; 5.5 Summary of Latency Control; References; 6 Crowdsourcing Database Systems and Optimization; 6.1 Overview of Crowdsourcing Database Systems; 6.2 Crowdsourcing Query Language; 6.2.1 CrowdDB; 6.2.2 Qurk; 6.2.3 Deco; 6.2.4 CDAS; 6.2.5 CDB; 6.3 Crowdsourcing Query Optimization; 6.3.1 CrowdDB; 6.3.2 Qurk; 6.3.3 Deco 6.3.4 CDAS6.3.5 CDB; 6.4 Summary of Crowdsourcing Database Systems; References; 7 Crowdsourced Operators; 7.1 Crowdsourced Selection; 7.1.1 Crowdsourced Filtering; 7.1.2 Crowdsourced Find; 7.1.3 Crowdsourced Search; 7.2 Crowdsourced Collection; 7.2.1 Crowdsourced Enumeration; 7.2.2 Crowdsourced Fill; 7.3 Crowdsourced Join (Crowdsourced Entity Resolution); 7.3.1 Background; 7.3.2 Candidate Set Generation; 7.3.3 Candidate Set Verification; 7.3.4 Human Interface for Join; 7.3.5 Other Approaches; 7.4 Crowdsourced Sort, Top-k, and Max/Min; 7.4.1 Workflow; 7.4.2 Pairwise Comparisons … (more)
- Publisher Details:
- Singapore : Springer
- Publication Date:
- 2018
- Extent:
- 1 online resource
- Subjects:
- 005.74
Computer science
Database management
Crowdsourcing
COMPUTERS / Databases / General
Computers -- Database Management -- General
Computers -- Expert Systems
Computers -- Database Management -- Data Mining
Databases
Expert systems / knowledge-based systems
Data mining
Mobile & handheld device programming / Apps programming
Big data
Software engineering
Data mining
Mobile computing
Electronic books - Languages:
- English
- ISBNs:
- 9789811078477
9811078475 - Related ISBNs:
- 9789811078460
- Notes:
- Note: Includes bibliographical references.
Note: Online resource; title from PDF title page (SpringerLink, viewed October 17, 2018). - Access Rights:
- Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
- Access Usage:
- Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD.DS.340699
- Ingest File:
- 01_290.xml