Proceedings of the 14th International Conference on Information Processing in Sensor Networks 2015
DOI: 10.1145/2737095.2737116
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Debiasing crowdsourced quantitative characteristics in local businesses and services

Abstract: Information about quantitative characteristics in local businesses and services, such as the number of people waiting in line in a cafe and the number of available fitness machines in a gym, is important for informed decision, crowd management and event detection. In this paper, we investigate the potential of leveraging crowds as sensors to report such quantitative characteristics and investigate how to recover the true quantity values from noisy crowdsourced information. Through experiments, we find that cro… Show more

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Cited by 36 publications
(32 citation statements)
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“…For ease of illustration, we list the notations used in this paper in Table 1. A typical quantitative crowdsourcing task is to ask crowd participants to count the number of target quantities such as people, vehicles, and animals in images, video frames, local businesses, or other scenarios [6]- [10]. Consider a scenario where M crowd participants u i make quantitative claims x ij (e.g., 5, 12, and 20) on N target quantities z j (e.g., the number of people in the jth image).…”
Section: Problem Statementmentioning
confidence: 99%
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“…For ease of illustration, we list the notations used in this paper in Table 1. A typical quantitative crowdsourcing task is to ask crowd participants to count the number of target quantities such as people, vehicles, and animals in images, video frames, local businesses, or other scenarios [6]- [10]. Consider a scenario where M crowd participants u i make quantitative claims x ij (e.g., 5, 12, and 20) on N target quantities z j (e.g., the number of people in the jth image).…”
Section: Problem Statementmentioning
confidence: 99%
“…In this section, we briefly review the Truth, Bias, and Precision (TBP) model proposed in [10], summarize its properties, outline the original truth discovery algorithm, and discuss its scalability issue.…”
Section: Review Of the Tbp Modelmentioning
confidence: 99%
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