• DocumentCode
    2251333
  • Title

    A Similarity Search Approach to Solving the Multi-query Problems

  • Author

    Shi, Yong ; Graham, Brian

  • Author_Institution
    Dept. of Comput. Sci., Kennesaw State Univ., Kennesaw, GA, USA
  • fYear
    2012
  • fDate
    May 30 2012-June 1 2012
  • Firstpage
    237
  • Lastpage
    242
  • Abstract
    In this paper, we present our research on similarity search problems. Similarity search problems define the distances between data points and a given query point Q, efficiently and effectively selecting data points which are closest to Q. It can be applied in various data mining fields. In many applications, information similar to multiple queries is required. In this paper, we explore the meaning of K nearest neighbors from a new perspective, define the distance between a data point and a query point set, and propose an algorithm to find nearest neighbors to multiple queries with possibly different degrees of importance. Our approach works for both full similarities and partial similarities in subsets of dimensions.
  • Keywords
    data mining; learning (artificial intelligence); query processing; set theory; K nearest neighbors; data mining fields; data point selection; multiquery problems; query point set; similarity search problems; Algorithm design and analysis; Indexes; Measurement; Nearest neighbor searches; Search problems; Signal processing algorithms; KNN; Multi-query; Similarity Search;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer and Information Science (ICIS), 2012 IEEE/ACIS 11th International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4673-1536-4
  • Type

    conf

  • DOI
    10.1109/ICIS.2012.17
  • Filename
    6211102