-PDF Download- Macro Task Crowdsourcing EBOOK

Macrotask Crowdsourcing

Author: Vassillis-Javed Khan

Publisher: Springer

Published: 2019-08-06

Total Pages: 279

ISBN-13: 3030123340

Crowdsourcing is an emerging paradigm that promises to transform several domains: creative work, business work, cultural cooperation, etc. Crowdsourcing reflects the close-knit interplay between the latest computer technologies, the rapidly changing work model of the 21st century, and the very nature of people. The interplay makes for an exciting but at the same time challenging new field to investigate under the lens of a diverse set of disciplines, ranging from the technical to the social and from the theoretical to the applied. Early research has focused on an aspect of crowdsourcing known as micro-tasking. Micro-tasks are simple tasks (like image annotations) that anyone could perform. An emerging area is how to utilize crowdsourcing to solve problems that go beyond simple tasks towards more complex ones, that require collaboration and creativity. In juxtaposition to micro-task crowdsourcing, this book investigates macro-task crowdsourcing and its potential.

Macro-task Crowdsourcing

Author: Vassillis-Javed Khan

Publisher:

Published: 2019

Total Pages:

ISBN-13: 9783030123352

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Macro Tasks in Crowdsourcing

Author: Arnaud Dierickx

Publisher:

Published: 2017-01-08

Total Pages: 68

ISBN-13: 9783659970122

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Crowdsourced Data Management

Author: Guoliang Li

Publisher: Springer

Published: 2018-10-12

Total Pages: 159

ISBN-13: 9811078475

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This book provides an overview of crowdsourced data management. Covering all aspects including the workflow, algorithms and research potential, it particularly focuses on the latest techniques and recent advances. The authors identify three key aspects in determining the performance of crowdsourced data management: quality control, cost control and latency control. By surveying and synthesizing a wide spectrum of studies on crowdsourced data management, the book outlines important factors that need to be considered to improve crowdsourced data management. It also introduces a practical crowdsourced-database-system design and presents a number of crowdsourced operators. Self-contained and covering theory, algorithms, techniques and applications, it is a valuable reference resource for researchers and students new to crowdsourced data management with a basic knowledge of data structures and databases.

Social Media and Crowdsourcing

Author: Sujoy Chatterjee

Publisher: CRC Press

Published: 2023-12-06

Total Pages: 259

ISBN-13: 1003804861

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Social media and crowdsourcing are important tools for solving complex problems. The benefit of crowdsourcing is that it leverages the power of human intelligence cost effectively and with less time. Social Media and Crowdsourcing: Application and Analytics examines the concepts of social media and crowdsourcing as well as their analytical aspects. It explores how these technologies contribute to the real world and examines such applications as promoting social good, agriculture, healthcare, tourism, disaster management, education, crime control, and cultural heritage. The book also looks at ethical issues in crowdsourcing and future scenarios and challenges for policy. Highlights of the book include the following: A crowdsourcing application in agriculture Crowdsourcing outline for a contemporary aided medicinal backup system Crowdsourcing-based recommendation in the tourism industry Crowdsourcing mechanisms for reviving cultural heritage Expanding the overarching concept of utilizing social media and crowdsourcing to solve various real-life problems, this book discusses how to bring together the wisdom of crowds for various decision-making problems in agriculture, disaster management, and healthcare. It addresses the various ethical issues arising out of various crowdsourcing-based applications. It puts forward diverse methodologies to involve crowdsourcing in education to implement new strategies to enhance learning outcomes. This book also addresses various problem-solving techniques for recommender applications in the travel and tourism industry. Providing a systematic discussion of the many sectors using crowdsourcing as an essential part of social innovation, this book is a theoretical and methodological look at the application of social media.

Crowdsourcing for Speech Processing

Author: Maxine Eskenazi

Publisher: John Wiley & Sons

Published: 2013-02-15

Total Pages: 343

ISBN-13: 1118541251

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Provides an insightful and practical introduction to crowdsourcing as a means of rapidly processing speech data Intended for those who want to get started in the domain and learn how to set up a task, what interfaces are available, how to assess the work, etc. as well as for those who already have used crowdsourcing and want to create better tasks and obtain better assessments of the work of the crowd. It will include screenshots to show examples of good and poor interfaces; examples of case studies in speech processing tasks, going through the task creation process, reviewing options in the interface, in the choice of medium (MTurk or other) and explaining choices, etc. Provides an insightful and practical introduction to crowdsourcing as a means of rapidly processing speech data. Addresses important aspects of this new technique that should be mastered before attempting a crowdsourcing application. Offers speech researchers the hope that they can spend much less time dealing with the data gathering/annotation bottleneck, leaving them to focus on the scientific issues. Readers will directly benefit from the book’s successful examples of how crowd- sourcing was implemented for speech processing, discussions of interface and processing choices that worked and choices that didn’t, and guidelines on how to play and record speech over the internet, how to design tasks, and how to assess workers. Essential reading for researchers and practitioners in speech research groups involved in speech processing

Crowdsourcing For Dummies

Author: David Alan Grier

Publisher: John Wiley & Sons

Published: 2013-03-27

Total Pages: 391

ISBN-13: 111994385X

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Give your business the edge with crowd-power! Crowdsourcing is an innovative way of outsourcing tasks, problems or requests to a group or community online. There are lots of ways business can use crowdsourcing to their advantage: be it crowdsourcing product ideas and development, design tasks, market research, testing, capturing or analyzing data, and even raising funds. It offers access to a wide pool of talent and ideas, and is an exciting way to engage the public with your business. Crowdsourcing For Dummies is your plain-English guide to making crowdsourcing, crowdfunding and open innovation work for you. It gives step-by-step advice on how to plan, start and manage a crowdsourcing project, where to crowdsource, how to find the perfect audience, how best to motivate your crowd, and tips for troubleshooting.

Managing Digital Open Innovation

Author: Pierre-jean Barlatier

Publisher: World Scientific

Published: 2020-05-13

Total Pages: 609

ISBN-13: 9811219249

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Recent developments of Internet-based digital technologies have revealed a huge potential of developing open, collaborative and network-centred innovation. However, firms face major challenges in using new technologies for rapid prototyping, data-mining, simulation, visualization, etc. to support their Open Innovation strategies.Responding to the need for further conceptual and empirical research on technology-enhanced open innovation, this book provides fresh and topical insights on how firms from different sectors have successfully implemented digital technologies for Open Innovation. Based on rich empirical data, this book discusses the benefits and drawbacks, the processes, the characteristics and the management practices of ICT-driven Open Innovation in private as well as public organizations.

Advanced Data Mining and Applications

Author: Guojun Gan

Publisher: Springer

Published: 2018-12-28

Total Pages: 538

ISBN-13: 3030050904

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This book constitutes the refereed proceedings of the 14th International Conference on Advanced Data Mining and Applications, ADMA 2018, held in Nanjing, China in November 2018. The 23 full and 22 short papers presented in this volume were carefully reviewed and selected from 104 submissions. The papers were organized in topical sections named: Data Mining Foundations; Big Data; Text and Multimedia Mining; Miscellaneous Topics.

Handbook on Federated Learning

Author: Saravanan Krishnan

Publisher: CRC Press

Published: 2024-01-09

Total Pages: 381

ISBN-13: 1003837522

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Mobile, wearable, and self-driving telephones are just a few examples of modern distributed networks that generate enormous amount of information every day. Due to the growing computing capacity of these devices as well as concerns over the transfer of private information, it has become important to process the part of the data locally by moving the learning methods and computing to the border of devices. Federated learning has developed as a model of education in these situations. Federated learning (FL) is an expert form of decentralized machine learning (ML). It is essential in areas like privacy, large-scale machine education and distribution. It is also based on the current stage of ICT and new hardware technology and is the next generation of artificial intelligence (AI). In FL, central ML model is built with all the data available in a centralised environment in the traditional machine learning. It works without problems when the predictions can be served by a central server. Users require fast responses in mobile computing, but the model processing happens at the sight of the server, thus taking too long. The model can be placed in the end-user device, but continuous learning is a challenge to overcome, as models are programmed in a complete dataset and the end-user device lacks access to the entire data package. Another challenge with traditional machine learning is that user data is aggregated at a central location where it violates local privacy policies laws and make the data more vulnerable to data violation. This book provides a comprehensive approach in federated learning for various aspects.