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Author:

Fang, Liying (Fang, Liying.) | Yan, Jianzhuo (Yan, Jianzhuo.) | Wang, Pu (Wang, Pu.)

Indexed by:

CPCI-S

Abstract:

Large scare redundant data in heterogeneous information integration systems creates computational challenges. In order to optimize the join order, a multi-copy join query optimization based on genetic algorithm is proposed. Choosing redundant copies of tables and searching for a good join order were represented by fitness function and genetic operators as well. Experimental results show that the multi-copy join query optimization is computationally efficient and necessary in information integration system.

Keyword:

information integration join order optimization genetic algorithm

Author Community:

  • [ 1 ] [Fang, Liying]Beijing Univ Technol, Coll Elect Informat & Control Engn, Beijing 100022, Peoples R China
  • [ 2 ] [Yan, Jianzhuo]Beijing Univ Technol, Coll Elect Informat & Control Engn, Beijing 100022, Peoples R China
  • [ 3 ] [Wang, Pu]Beijing Univ Technol, Coll Elect Informat & Control Engn, Beijing 100022, Peoples R China

Reprint Author's Address:

  • [Wang, Pu]Beijing Univ Technol, Coll Elect Informat & Control Engn, Beijing 100022, Peoples R China

Email:

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Source :

ADVANCING SCIENCE THROUGH COMPUTATION

Year: 2008

Page: 339-343

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 6

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