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Approximating the Wisdom of the Crowd
| Content Provider | CiteSeerX |
|---|---|
| Author | Hirsh, Haym Rudin, Cynthia |
| Abstract | The problem of “approximating the crowd ” is that of estimating the crowd’s majority opinion by querying only a subset of it. Algorithms that approximate the crowd can intelligently stretch a limited budget for a crowdsourcing task. We present an algorithm, “CrowdSense, ” that works in an online fashion to dynamically sample subsets of labelers based on an exploration/exploitation criterion. The algorithm produces a weighted combination of the labelers ’ votes that approximates the crowd’s opinion. 1 |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Sample Subset Limited Budget Weighted Combination Crowd Opinion Crowd Majority Opinion Online Fashion Crowdsourcing Task Exploration Exploitation Criterion |
| Content Type | Text |
