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Crowdsourcing and Its Applications on Data Mining : A Brief Survey
Authors(2) :-K. Karthika, R. Durga Devi
Crowdsourcing allows large-scale and flexible invocation of human input for data gathering and analysis, which introduces a new paradigm of data mining process. Traditional data mining methods often require the experts in analytic domains to annotate the data. However, it is expensive and usually takes a long time. Crowdsourcing enables the use of heterogeneous background knowledge from volunteers and distributes the annotation process to small portions of efforts from different contributions. This paper reviews the state-of-the-arts on the crowdsourcing for data mining in recent years. We first review the challenges and opportunities of data mining tasks using crowdsourcing, and summarize the framework of them. Then we highlight several exemplars works in each component of the framework, including question designing, data mining and quality control. Finally, we conclude the limitation of crowdsourcing for data mining and suggest related areas for future research
K. Karthika, R. Durga Devi
Clustering, Crowdsourcing, Data mining, Sampling, Quality control
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Published in : Volume 4 | Issue 2 | January-February 2018
Date of Publication : 2018-02-28
License: This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 24-29
Manuscript Number : IJSRST18414
Publisher : Technoscience Academy
PRINT ISSN : 2395-6011
ONLINE ISSN : 2395-602X
Cite This Article :
K. Karthika, R. Durga Devi, "Crowdsourcing and Its Applications on Data Mining : A Brief Survey", International Journal of Scientific Research in Science and Technology(IJSRST), Print ISSN : 2395-6011, Online ISSN : 2395-602X, Volume 4, Issue 2, pp.24-29, January-February-2018.
Journal URL : http://ijsrst.com/IJSRST18414