• DocumentCode
    3258036
  • Title

    Similarity Search Problem Research on Multi-dimensional Data Sets

  • Author

    Yong Shi ; Graham, Brian

  • Author_Institution
    Dept. of Comput. Sci., Kennesaw State Univ., Kennesaw, GA, USA
  • fYear
    2013
  • fDate
    15-17 April 2013
  • Firstpage
    573
  • Lastpage
    577
  • Abstract
    In this paper, we present our continuous work on designing an algorithm to find nearest neighbors to given queries. In our previous work, we analyze the situation that there are multiple queries with different level of importance, and define a weight for each query point. We also propose an algorithm to find nearest neighbors to multiple queries with weights and enhanced our algorithm based on query point distribution. In this paper we analyze the data distribution on various dimensions, and apply the shrinking concept for the improvement and enhancement of our multi-query search approach.
  • Keywords
    data handling; query processing; search problems; data distribution; multidimensional data sets; multiple queries; multiquery search approach; nearest neighbors; query point distribution; similarity search problem research; Accuracy; Algorithm design and analysis; Data mining; Data preprocessing; Histograms; Nearest neighbor searches; Search problems; K Nearest Search; Multi-query; Similarity Search;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Technology: New Generations (ITNG), 2013 Tenth International Conference on
  • Conference_Location
    Las Vegas, NV
  • Print_ISBN
    978-0-7695-4967-5
  • Type

    conf

  • DOI
    10.1109/ITNG.2013.72
  • Filename
    6614367