• DocumentCode
    659397
  • Title

    Using crowdsourcing for data analytics

  • Author

    Garcia-Molina, Hector

  • Author_Institution
    Stanford Univ., Stanford, CA, USA
  • fYear
    2013
  • fDate
    6-9 Oct. 2013
  • Firstpage
    4
  • Lastpage
    4
  • 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;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Big Data, 2013 IEEE International Conference on
  • Conference_Location
    Silicon Valley, CA
  • Type

    conf

  • DOI
    10.1109/BigData.2013.6691546
  • Filename
    6691546
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=659397