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A Framework for Extracting Reliable Information from Unstructured Uncertain Big Data

Part of the Smart Innovation, Systems and Technologies book series (SIST,volume 57)

Abstract

Big Data is still in its initial stages and has prompted various basic issues and difficulties to rise, for example, the pace of exchange, information development, and assorted qualities of information and security issues. For example, overseeing and abusing immense measures of information make it more valuable and important has turned into a test driving basic learning for choice making and in picking up an understanding into the general circumstance. Huge information has gotten phenomenal consideration from open and private sectors and in addition from the educated community around the world. In advertising, enormous information is utilized to comprehend the practices and actives of clients. In the experimental fields, huge information can be misused by aiding and taking care of the issues confronting the investigative fields extending from nanotechnology to climatology to geophysics. In the field of law requirement, social administrations and country security, enormous information has exhibited its handiness for government organizations to bolster in their choice making.

Keywords

  • Big data
  • Unstructured data
  • Uncertain data
  • Extracting reliable information

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Correspondence to Sanjay Kumar Singh .

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Singh, S.K., Mani, N., Singh, B. (2016). A Framework for Extracting Reliable Information from Unstructured Uncertain Big Data. In: Czarnowski, I., Caballero, A., Howlett, R., Jain, L. (eds) Intelligent Decision Technologies 2016. Smart Innovation, Systems and Technologies, vol 57. Springer, Cham. https://doi.org/10.1007/978-3-319-39627-9_16

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