CrowdScreen
作者： Aditya G. Parameswaran , Hector Garcia-Molina , Hyunjung Park , Neoklis Polyzotis , Aditya Ramesh
关键词: Set (abstract data type) 、 Computer science 、 Artificial intelligence 、 Heuristics 、 Probabilistic analysis of algorithms 、 Large set (Ramsey theory) 、 State (computer science) 、 Machine learning 、 Algorithm 、 Variety (cybernetics) 、 Theoretical computer science 、 Crowdsourcing
摘要: Given a large set of data items, we consider the problem filtering them based on properties that can be verified by humans. This is commonplace in crowdsourcing applications, and yet, to our knowledge, no one has considered formal optimization this problem. (Typical solutions use heuristics solve problem.) We formally state few different variants develop deterministic probabilistic algorithms optimize expected cost (i.e., number questions) error. experimentally show provide definite gains with respect other strategies. Our applied variety scenarios form an integral part any query processor uses human computation.
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sci-hub.se 参考文章(21)
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