Data-driven crowdsourcing: Management, mining, and applications

Lei Chen, Dongwon Lee, Tova Milo

Research output: Contribution to journalConference articlepeer-review

13 Scopus citations


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 languageEnglish (US)
Pages (from-to)1527-1529
Number of pages3
JournalProceedings - International Conference on Data Engineering
StatePublished - 2015
Event2015 31st IEEE International Conference on Data Engineering, ICDE 2015 - Seoul, Korea, Republic of
Duration: Apr 13 2015Apr 17 2015

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Information Systems


Dive into the research topics of 'Data-driven crowdsourcing: Management, mining, and applications'. Together they form a unique fingerprint.

Cite this