Crowdsourced Data Management: Industry and Academic Perspectives

Crowdsourced Data Management Industry and Academic Perspectives Crowdsourcing and human computation enable organizations to accomplish tasks that are currently not possible for fully automated techniques to complete or require flexibility and scalability than tra

Crowdsourced Data Management A Survey crowdsourced tasks, developing crowdsourced data manipulation operators, and optimizing plans consisting of multiple operators In this paper, we survey and synthesize a wide spectrum of existing studies on crowdsourced data management Based on this analysis Crowdsourced Data Management Industry and Academic powered data processing is a large and growing eld Over the next decade, we believe that most technical organizations will in some way bene t from crowd work, and hope that this book can help guide the effective adoption of crowdsourcing across these organizations A Marcus and A Parameswaran Crowdsourced Data Management Industry and Crowdsourced Data Management A Survey IEEE Journals Crowdsourced Data Management A Survey Abstract Any important data management and analytics tasks cannot be completely addressed by automated processes These tasks, such as entity resolution, sentiment analysis, and image recognition can Crowdsourced Data Management Overview and Challenges ing studies on crowdsourced data management We rst give an overview of crowdsourcing, and then summarize the fundamental techniques, including quality control, cost control, and latency con trol, which must be considered in crowdsourced data management Next we review crowdsourced operators, including selection, col Crowdsourced Data Management A Survey IEEE Conference Crowdsourced Data Management A Survey Abstract Many important data management and analytics tasks cannot be completely addressed by automated processes These tasks, such as entity resolution, sentiment analysis, and image recognition can now publishers Crowdsourced Data Management Industry Crowdsourced Data Management Industry and Academic Perspectives aims to narrow the gap between academics and practitioners On the academic side, it summarizes the state of the art in crowd powered algorithms and system design tailored to large scale data processing.

  • Title: Crowdsourced Data Management: Industry and Academic Perspectives
  • Author: Adam Marcus Aditya Parameswaran
  • ISBN: 9781680830903
  • Page: 369
  • Format: Paperback
  • Crowdsourcing and human computation enable organizations to accomplish tasks that are currently not possible for fully automated techniques to complete, or require flexibility and scalability than traditional employment relationships can facilitate In the area of data processing, companies have benefited from crowd workers on platforms such as s Mechanical TurCrowdsourcing and human computation enable organizations to accomplish tasks that are currently not possible for fully automated techniques to complete, or require flexibility and scalability than traditional employment relationships can facilitate In the area of data processing, companies have benefited from crowd workers on platforms such as s Mechanical Turk or Upwork to complete tasks as varied as content moderation, web content extraction, entity resolution, and video audio image processing Several academic researchers from diverse areas, ranging from the social sciences to computer science, have embraced crowdsourcing as a research area, resulting in algorithms and systems that improve crowd work quality, latency, and cost Despite the relative nascence of the field, the academic and the practitioner communities have largely operated independently of each other for the past decade, rarely exchanging techniques and experiences Crowdsourced Data Management Industry and Academic Perspectives aims to narrow the gap between academics and practitioners On the academic side, it summarizes the state of the art in crowd powered algorithms and system design tailored to large scale data processing On the industry side, it surveys 13 industry users such as Google, Facebook, and Microsoft and four marketplace providers of crowd work such as CrowdFlower and Upwork to identify how hundreds of engineers and tens of million dollars are invested in various crowdsourcing solutions Crowdsourced Data Management Industry and Academic Perspectives simultaneously introduces academics to real problems that practitioners encounter every day, and provides a survey of the state of the art for practitioners to incorporate into their designs Through the surveys, it also highlights the fact that crowdpowered data processing is a large and growing field Over the next decade, most technical organizations are likely to benefit in some way from crowd work, and this monograph can help guide the effective adoption of crowdsourcing across these organizations.

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