• DocumentCode
    1707039
  • Title

    A Fast Biological Data Mining Algorithm Based on Embedded Frequent Subtree

  • Author

    Yang, Zhong-xue

  • Author_Institution
    Dept. of Inf. Technol., Nanjing Xiaozhuang Coll., Nanjing, China
  • fYear
    2010
  • Firstpage
    705
  • Lastpage
    709
  • Abstract
    In this paper, we present a fast biological data mining algorithm named IRTM based on embedded frequent subtree. We also advance a string encoding method for representing the trees, a scope-list for extending all substrings and some pruning rules which can further reduce the computational time and space cost. Experimental results show that IRTM algorithm can achieve significantly performance improvement over previous works.
  • Keywords
    biology computing; data mining; string matching; trees (mathematics); IRTM; biological data mining; embedded frequent subtree; string encoding; Algorithm design and analysis; Biological information theory; Data mining; Databases; Encoding; RNA; Biological data;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia Information Networking and Security (MINES), 2010 International Conference on
  • Conference_Location
    Nanjing, Jiangsu
  • Print_ISBN
    978-1-4244-8626-7
  • Electronic_ISBN
    978-0-7695-4258-4
  • Type

    conf

  • DOI
    10.1109/MINES.2010.152
  • Filename
    5671153
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1707039