Data-driven crowdsourcing: Management, mining, and applications

Lei Chen, Dongwon Lee, Tova Milo

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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 languageEnglish
Title of host publication2015 IEEE 31st International Conference on Data Engineering
PublisherIEEE Computer Society
Pages1527-1529
Number of pages3
ISBN (Electronic)978-1-4799-7964-6
DOIs
StatePublished - 2015
Event2015 31st IEEE International Conference on Data Engineering, ICDE 2015 - Seoul, Korea, Republic of
Duration: 13 Apr 201517 Apr 2015

Publication series

NameProceedings - International Conference on Data Engineering

Conference

Conference2015 31st IEEE International Conference on Data Engineering, ICDE 2015
Country/TerritoryKorea, Republic of
CitySeoul
Period13/04/1517/04/15

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Information Systems

Fingerprint

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

Cite this