Human computation tasks with global constraints
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Miller_Human computation.pdf
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2.04 MB
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Adobe PDF
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Author(s)
Zhang, Haoqi
Law, Edith
Miller, Robert C.
Gajos, Krzysztof Z.
Parkes, David C.
Horvitz, Eric
Date Issued
May 2012
Journal
Proceedings of the 2012 ACM Annual Conference on Human Factors in Computing Systems (CHI '12)
Publisher
Association for Computing Machinery (ACM)
Citation
Haoqi Zhang, Edith Law, Rob Miller, Krzysztof Gajos, David Parkes, and Eric Horvitz. 2012. Human computation tasks with global constraints. In Proceedings of the 2012 ACM annual conference on Human Factors in Computing Systems (CHI '12). ACM, New York, NY, USA, 217-226.
Version
Author's final manuscript
Abstract
An important class of tasks that are underexplored in current human computation systems are complex tasks with global constraints. One example of such a task is itinerary planning, where solutions consist of a sequence of activities that meet requirements specified by the requester. In this paper, we focus on the crowdsourcing of such plans as a case study of constraint-based human computation tasks and introduce a collaborative planning system called Mobi that illustrates a novel crowdware paradigm. Mobi presents a single interface that enables crowd participants to view the current solution context and make appropriate contributions based on current needs. We conduct experiments that explain how Mobi enables a crowd to effectively and collaboratively resolve global constraints, and discuss how the design principles behind Mobi can more generally facilitate a crowd to tackle problems involving global constraints.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike 3.0
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DOI of Published Version
https://doi.org/10.1145/2207676.2207708
