Title :
Using crowdsourcing for data analytics
Author :
Garcia-Molina, Hector
Author_Institution :
Stanford Univ., Stanford, CA, USA
Abstract :
Summary form only given. It may sound contradictory to use humans to analyze big data, since humans cannot process huge amounts of data, may be error prone and are relatively slow. However, humans can do certain tasks much better than machines, e.g., tasks that involve image analysis or natural language. In this talk I will discuss how humans can be judiciously used to improve data analytics by cleansing, clustering and filtering critical data. I will also briefly describe ongoing work at our Stanford InfoLab in this area.
Keywords :
data analysis; information filtering; pattern clustering; Stanford InfoLab; big data analysis; critical data cleansing; critical data clustering; critical data filtering; crowdsourcing; data analytics; image analysis; natural language;
Conference_Titel :
Big Data, 2013 IEEE International Conference on
Conference_Location :
Silicon Valley, CA
DOI :
10.1109/BigData.2013.6691546
