Schall Service-Oriented Crowdsourcing

Architecture, Protocols and Algorithms
2012
ISBN: 978-1-4614-5956-9
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 94 Seiten

Reihe: SpringerBriefs in Computer Science

At a fundamental level, service-oriented crowdsourcing applies the principles of service-oriented architecture (SOA) to the discovery, composition and selection of a scalable human workforce. Service-Oriented Crowdsourcing: Architecture, Protocols and Algorithms provides both an analysis of contemporary crowdsourcing systems, such as Amazon Mechanical Turk, and a statistical description of task-based marketplaces. The book also introduces a novel mixed service-oriented computing paradigm by providing an architectural description of the Human-Provided Services (HPS) framework and the application of social principles to human coordination and delegation actions. Finally, it examines previously investigated concepts and applies them to business process management integration, including the extension of XML-based industry standards and the instantiation of flexible processes in crowdsourcing environments. Service-Oriented Crowdsourcing is intended for researchers and other academics as an in-depth guide to developing new applications based on crowdsourcing platforms and evaluating various selection and ranking algorithms. Practitioners and other industry professionals will also find this book invaluable.

Autoren/Hrsg.

Schall, Daniel

Inhaltsverzeichnis

1;Preface;5
2;Acknowledgments;6
3;Contents;7
4;Acronyms;9
5;1 Introduction;10
5.1;1.1 Overview;10
5.2;1.2 Task Marketplaces;11
5.3;1.3 SOA for Crowdsourcing;11
5.4;1.4 Adaptive Processes;13
5.5;1.5 Outline;13
5.6;References;14
6;2 Crowdsourcing Task Marketplaces;15
6.1;2.1 Introduction;15
6.2;2.2 Background;16
6.3;2.3 Basic Model and Statistics;18
6.3.1;2.3.1 System Context Overview;18
6.3.2;2.3.2 Marketplace Task Statistics;19
6.4;2.4 Clustering and Community Detection;22
6.4.1;2.4.1 Clustering Approach;22
6.4.2;2.4.2 Community-Based Ranking Model;24
6.5;2.5 Crowdsourcing Broker Discovery;25
6.6;2.6 Experiments;27
6.6.1;2.6.1 Community Discovery and Ranking;27
6.6.2;2.6.2 Recommendation of Crowdsourcing Brokers;30
6.7;2.7 Conclusion and Future Work;35
6.8;References;35
7;3 Human-Provided Services;39
7.1;3.1 Introduction;39
7.2;3.2 Background;40
7.3;3.3 HPS Interaction Model;42
7.3.1;3.3.1 HPS Activity Model;42
7.3.2;3.3.2 Hierarchical Activities;44
7.3.3;3.3.3 Task Model;45
7.3.4;3.3.4 Task Execution Model;46
7.4;3.4 Architecture;47
7.4.1;3.4.1 HPS Framework;48
7.4.2;3.4.2 Data Collections;50
7.4.3;3.4.3 Interactions and Monitoring;51
7.5;3.5 Expertise Ranking;53
7.5.1;3.5.1 Context-Sensitive Interaction Mining;53
7.5.2;3.5.2 Hubs and Authorities;54
7.5.3;3.5.3 Personalized Expert Queries;55
7.5.4;3.5.4 Ranking Model;56
7.6;3.6 Evaluation;59
7.6.1;3.6.1 SOA Testbed Environment;59
7.6.2;3.6.2 Performance Aspects;60
7.6.3;3.6.3 Quality of Expertise Rankings;62
7.7;3.7 Conclusion and Future Work;64
7.8;References;64
8;4 Crowdsourcing Tasks in BPEL4People;67
8.1;4.1 Introduction;67
8.2;4.2 Background;68
8.3;4.3 Service-Oriented Crowdsourcing;70
8.3.1;4.3.1 Task-Based Crowdsourcing Markets;70
8.3.2;4.3.2 Approach Outline;71
8.4;4.4 Non-Functional Properties in B4P;73
8.4.1;4.4.1 Human Tasks in B4P;74
8.4.2;4.4.2 Basic Model and Extensions;75
8.5;4.5 Social Aggregator;79
8.6;4.6 Task Segmentation and Matching;81
8.6.1;4.6.1 Hierarchical Crowd Activities;81
8.6.2;4.6.2 Social Interactions;82
8.6.3;4.6.3 Ranking Coordinators;84
8.7;4.7 Implementation and Evaluation;89
8.7.1;4.7.1 SOA-Based Crowdsourcing Environment;89
8.7.2;4.7.2 Social Network Generation;93
8.7.3;4.7.3 Discussion;94
8.7.4;4.7.4 Overall Findings;96
8.8;4.8 Conclusion and Future Work;98
8.9;References;98
9;5 Conclusion;101