Crowdsourced data enumeration, in which the Web crowd is requested to enumerate data items within a specified range, is important in many Web applications such as hotel reviews. This paper presents a processing method for crowdsourced data enumeration on microtask-based crowdsourcing platforms. A general approach to achieving a high recall in data enumeration is to apply the divide-and-conquer principle. However, how to apply the principle to data enumeration on microtask-based crowdsourcing platforms is not trivial. The proposed method is unique in that the workers join the process of generating smaller tasks in a divide-and-conquer fashion, and the programmer does not need to provide many microtasks in advance. This paper explains the method, provides theoretical results to show the method works well with microtask-based platforms, and explains our experimental results that suggest the proposed method can achieve higher recalls and produces appropriate tasks for microtask-based crowdsourcing. © 2013 Springer International Publishing.
CITATION STYLE
Aoki, H., & Morishima, A. (2013). A divide-and-conquer approach for crowdsourced data enumeration. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8238 LNCS, pp. 60–74). https://doi.org/10.1007/978-3-319-03260-3_6
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