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"Constrained crowd judgment analysis" by Sujoy Chatterjee, Anirban Mukhopadhyay and Malay Bhattacharyya with Martin Vesely as coordinator

Published:27 November 2017Publication History
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Abstract

Leveraging the online crowd replacing limited experts has become a successful practice over the last decade for solving diverse real-life problems. Various complex problems are now being solved utilizing the power of crowd, an approach popularly termed as 'crowdsourcing'. Judgment analysis refers to a particular type of crowdsourcing task where we aggregate the opinions collected from the crowd for a purpose. We, being the rational agents, have a common interest towards knowing others' opinions before providing our own. This broadly categorizes the problem of judgment analysis into two types --- with independent and with dependent opinions. However, a new paradigm of crowd based judgment analysis has recently evolved, which can tackle the constrained opinions of crowd workers. In this article, we touch upon this novel problem of constrained crowd judgment analysis and discuss its possible dimensions of research.

References

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  • Published in

    cover image ACM SIGWEB Newsletter
    ACM SIGWEB Newsletter  Volume 2017, Issue Autumn
    Autumn 2017
    21 pages
    ISSN:1931-1745
    EISSN:1931-1435
    DOI:10.1145/3146484
    Issue’s Table of Contents

    Copyright © 2017 Copyright is held by the owner/author(s)

    Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    • Published: 27 November 2017

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