Personalized Task Recommendation in Crowdsourcing Systems
Softcover reprint of the original 1st ed. 2016
by
David Geiger
Book Details
Format
Paperback / Softback
Book Series
Progress in IS
ISBN-10
3319370588
ISBN-13
9783319370583
Edition
Softcover reprint of the original 1st ed. 2016
Publisher
Springer International Publishing AG
Imprint
Springer International Publishing AG
Country of Manufacture
CH
Country of Publication
GB
Publication Date
Aug 23rd, 2016
Print length
108 Pages
Product Classification:
Business mathematics & systemsBusiness mathematics and systemsDigital and Information technology: general topicsInformation technology: general issuesBusiness applicationsData miningArtificial intelligenceArtificial intelligence (AI)Expert systems / knowledge-based systemsHuman-computer interactionHuman–computer interaction
Ksh 8,100.00
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This book examines the principles of and advances in personalized task recommendation in crowdsourcing systems, with the aim of improving their overall efficiency.
This book examines the principles of and advances in personalized task recommendation in crowdsourcing systems, with the aim of improving their overall efficiency. It discusses the challenges faced by personalized task recommendation when crowdsourcing systems channel human workforces, knowledge, skills and perspectives beyond traditional organizational boundaries. The solutions presented help interested individuals find tasks that closely match their personal interests and capabilities in a context of ever-increasing opportunities of participating in crowdsourcing activities. In order to explore the design of mechanisms that generate task recommendations based on individual preferences, the book first lays out a conceptual framework that guides the analysis and design of crowdsourcing systems. Based on a comprehensive review of existing research, it then develops and evaluates a new kind of task recommendation service that integrates with existing systems. The resulting prototype provides a platform for both the field study and the practical implementation of task recommendation in productive environments.
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