short-paper

Network based mechanisms for competitive crowdsourcing

Authors:

Sankar Kumar Mridha,

Malay BhattacharyyaAuthors Info & Claims

CODS-COMAD '18: Proceedings of the ACM India Joint International Conference on Data Science and Management of Data

Pages 318 - 321

https://doi.org/10.1145/3152494.3167979

Published: 11 January 2018 Publication History

Abstract

The working principle of crowd in a crowdsourcing platform is either competitive or collaborative. Occasionally, the tasks submitted to crowdsourcing environments are decomposable. They are challenging to solve because decomposition and composition of tasks and proper selection of workers are difficult. We show that by appropriate inclusion of collaboration in a competitive crowdsourcing environment, we can handle decomposable-type tasks given with posted-price in a better way. We initially attempt to manage 2-decomposable tasks with appropriate mechanism design. Extending it further to n-decomposable tasks, we propose a network based mechanism to choose the best mixture of sub-tasks in a competitive environment for selecting the winners. We are currently interested in developing mechanisms to remove the participation bias from such environments.

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Cited By

Kumar SPandey S(2024) WSC : A Crowd‐Powered Framework for Mapping Decomposable Complex‐Task With Worker‐Set Concurrency and Computation: Practice and Experience10.1002/cpe.8305Online publication date: 21-Oct-2024
https://doi.org/10.1002/cpe.8305
Hasteer NSindhwani RBehl AVarshney ASharma A(2023)Exploring the inhibitors for competitive AI software development through cloud driven transformationAnnals of Operations Research10.1007/s10479-023-05619-5342:1(355-397)Online publication date: 18-Oct-2023
https://doi.org/10.1007/s10479-023-05619-5
Bhattacharya BDey LChaudhury SKrishnapuram RSingla PRoy R(2019)Quality Enhancement in CrowdsourcingProceedings of the ACM India Joint International Conference on Data Science and Management of Data10.1145/3297001.3297058(346-349)Online publication date: 3-Jan-2019
https://dl.acm.org/doi/10.1145/3297001.3297058
Show More Cited By

Index Terms

Network based mechanisms for competitive crowdsourcing
1. Human-centered computing
  1. Collaborative and social computing
    1. Collaborative and social computing theory, concepts and paradigms
      1. Computer supported cooperative work
2. Information systems
  1. World Wide Web
    1. Web applications
      1. Crowdsourcing

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Published In

cover image ACM Other conferences

CODS-COMAD '18: Proceedings of the ACM India Joint International Conference on Data Science and Management of Data

January 2018

379 pages

ISBN:9781450363419

DOI:10.1145/3152494

Conference Chair:
Sayan Ranu
IIT Delhi
,
General Chairs:
Niloy Ganguly
IIT Kharagpur
,
Raghu Ramakrishnan
Microsoft
,
Program Chairs:
Sunita Sarawagi
IIT Bombay
,
Shourya Roy
American Express Big Data Labs

Copyright © 2018 ACM.

Permission to make digital or hard copies of all or part 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 components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 11 January 2018

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Short-paper

Funding Sources

MeitY, Government of India

Conference

CoDS-COMAD '18

CoDS-COMAD '18: The ACM India Joint International Conference on Data Science & Management of Data

January 11 - 13, 2018

Goa, India

Acceptance Rates

CODS-COMAD '18 Paper Acceptance Rate 50 of 150 submissions, 33%;

Overall Acceptance Rate 197 of 680 submissions, 29%

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Cited By

Kumar SPandey S(2024) WSC : A Crowd‐Powered Framework for Mapping Decomposable Complex‐Task With Worker‐Set Concurrency and Computation: Practice and Experience10.1002/cpe.8305Online publication date: 21-Oct-2024
https://doi.org/10.1002/cpe.8305
Hasteer NSindhwani RBehl AVarshney ASharma A(2023)Exploring the inhibitors for competitive AI software development through cloud driven transformationAnnals of Operations Research10.1007/s10479-023-05619-5342:1(355-397)Online publication date: 18-Oct-2023
https://doi.org/10.1007/s10479-023-05619-5
Bhattacharya BDey LChaudhury SKrishnapuram RSingla PRoy R(2019)Quality Enhancement in CrowdsourcingProceedings of the ACM India Joint International Conference on Data Science and Management of Data10.1145/3297001.3297058(346-349)Online publication date: 3-Jan-2019
https://dl.acm.org/doi/10.1145/3297001.3297058
Mridha SBhattacharyya M(2018)A network based mechanism for managing decomposable tasks via crowdsourcingElectronic Commerce Research10.1007/s10660-018-9317-818:4(869-881)Online publication date: 1-Dec-2018
https://dl.acm.org/doi/10.1007/s10660-018-9317-8
Gong DPeng CZhao XLin Q(2018)A Method of Accurately Accepting Tasks for New Workers Incorporating with Capacities and Competition IntensitiesBio-inspired Computing: Theories and Applications10.1007/978-981-13-2829-9_18(188-200)Online publication date: 6-Oct-2018
https://doi.org/10.1007/978-981-13-2829-9_18

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