PSNM: An Algorithm for Detecting Duplicates in Oceanographic Data

  • L. Srinivasa Reddy
  • S. P. Vighneshwar
  • B. Ravikiran
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 5)


This work discusses a new method of identifying duplicates in surface meteorology data using PSNM (Progressive Sorted Neighborhood Method) Algorithm. Duplicate detection is the process of identifying the same representations of the real world entities in the data. This method needs to process a large amount of ocean data sets in shorter time. PSNM algorithm increases the efficiency of finding duplicates with lesser execution time and get the efficient results much earlier than traditional approaches. It is observed that all possible duplicates associated with the data can be identified using this method, and also this work proposes a new way to access the resulted (Duplicate eliminated) data using authorization restrictions based on the type of user and their need with different file conversion formats.


Duplicate detection PSNM CTD Data cleaning 



This work was completed in INCOIS Hyderabad. The Authors wish to thank Director ESSO-INCOIS, Hyderabad for the encouragement and facilities provided and also Authors wish to thank scientists for their support and guidance throughout working on this project and preparing this manuscript. We would also like to express our gratitude to our Professors in the college and Prof. S.C. Satapathy (Head of Dept.), ANITS, Visakhapatnam for his continuous support and encouragement.


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Copyright information

© Springer Nature Singapore Pte Ltd. 2017

Authors and Affiliations

  • L. Srinivasa Reddy
    • 1
  • S. P. Vighneshwar
    • 2
  • B. Ravikiran
    • 1
  1. 1.Computer Science and Technology, Department of CSEANIL Neerukonda Institute of Technology and Sciences (ANITS)VisakhapatnamIndia
  2. 2.Computational Facilities and Web Based Services Group (CWG)Indian National Centre for Ocean Information Services (INCOIS)HyderabadIndia

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