Data-driven crowdsourcing: Management, mining, and applications

Lei Chen; Dongwon Lee; Tova Milo

doi:10.1109/ICDE.2015.7113418

Data-driven crowdsourcing: Management, mining, and applications

Lei Chen, Dongwon Lee, Tova Milo

Research output: Contribution to journal › Conference article › peer-review

14 Scopus citations

Abstract

In this 3-hour tutorial, we present the landscape of recent developments in data management and mining research, and survey a selected set of state-of-the-art works that significantly extended existing database reserach in order to incorporate and exploit the novel notion of “crowdsourcing” in a creative fashion. In particular, three speakers take turns to present the topics of human-powered database operations, crowdsourced data mining, and the application of crowdsourcing in social media, respectively.

Original language	English (US)
Pages (from-to)	1527-1529
Number of pages	3
Journal	Proceedings - International Conference on Data Engineering
Volume	2015-January
DOIs	https://doi.org/10.1109/ICDE.2015.7113418
State	Published - 2015
Event	2015 31st IEEE International Conference on Data Engineering, ICDE 2015 - Seoul, Korea, Republic of Duration: Apr 13 2015 → Apr 17 2015

All Science Journal Classification (ASJC) codes

Software
Signal Processing
Information Systems

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10.1109/ICDE.2015.7113418

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abstract = "In this 3-hour tutorial, we present the landscape of recent developments in data management and mining research, and survey a selected set of state-of-the-art works that significantly extended existing database reserach in order to incorporate and exploit the novel notion of “crowdsourcing” in a creative fashion. In particular, three speakers take turns to present the topics of human-powered database operations, crowdsourced data mining, and the application of crowdsourcing in social media, respectively.",

author = "Lei Chen and Dongwon Lee and Tova Milo",

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Data-driven crowdsourcing: Management, mining, and applications

Abstract

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