AAAI Publications, 2017 AAAI Spring Symposium Series

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Smart City Planning with Constrained Crowd Judgment Analysis
Sujoy Chatterjee, Anirban Mukhopadhyay, Malay Bhattacharyya

Last modified: 2017-03-20


Collecting opinions from multiple crowd workers has been proved to be very effective to reach into a prompt and robust decision. There are many real-life applications (like smart city planning and urban development) where public (skilled or unskilled) opinions play a better role in comparison with single expert opinion. A spectrum of algorithms has already been proposed for obtaining robust consensus judgment from multiple crowd opinions. In most of the problems, for a particular question we receive a single opinion with multiple options. But in this article, we have proposed a new research problem termed as constrained judgment analysis problem that consists of the questions having multiple opinions. Moreover, some constraints among the options are required to be satisfied while giving opinions. In this constrained judgment analysis, the traditional way of decision making, like majority voting, weighted voting or probablistic model, cannot be applied directly due to the purpose of constraint satisfaction. In this work, we have also proposed a probabilistic method for obtaining final solution for constrained judgment analysis problem and demonstrated its efficacy over a synthetic dataset, thereby proving its utility in resource allocation for smart city planning.

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