• DocumentCode
    1553400
  • Title

    Efficient processing of nested Fuzzy SQL queries in a fuzzy database

  • Author

    Yang, Qi ; Zhang, Weining ; Liu, Chengwen ; Wu, Jing ; Yu, Clement ; Nakajima, Hiroshi ; Rishe, Naphtali David

  • Author_Institution
    Dept. of Comput. Sci., Wisconsin Univ., Platteville, WI, USA
  • Volume
    13
  • Issue
    6
  • fYear
    2001
  • Firstpage
    884
  • Lastpage
    901
  • Abstract
    In a fuzzy relational database where a relation is a fuzzy set of tuples and ill-known data are represented by possibility distributions, nested fuzzy queries can be expressed in the Fuzzy SQL language. Although it provides a very convenient way for users to express complex queries, a nested fuzzy query may be very inefficient to process with the naive evaluation method based on its semantics. In conventional databases, nested queries are unnested to improve the efficiency of their evaluation. In this paper, we extend the unnesting techniques to process several types of nested fuzzy queries. An extended merge-join is used to evaluate the unnested fuzzy queries. As shown by both theoretical analysis and experimental results, the unnesting techniques with the extended merge-join significantly improve the performance of evaluating nested fuzzy queries
  • Keywords
    SQL; fuzzy set theory; merging; query processing; relational databases; Fuzzy SQL language; extended merge-join; fuzzy relational database; fuzzy tuple set; nested fuzzy SQL query processing; possibility distributions; unnesting techniques; Computer Society; Computer science; Data models; Database systems; Fuzzy set theory; Fuzzy sets; Fuzzy systems; Performance analysis; Query processing; Relational databases;
  • fLanguage
    English
  • Journal_Title
    Knowledge and Data Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1041-4347
  • Type

    jour

  • DOI
    10.1109/69.971185
  • Filename
    971185