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Design and Development of a Cross Search Engine for Multiple Heterogeneous Databases Using UML and Design Patterns

Author

Listed:
  • Min Song

    (Drexel University)

  • Il-Yeol Song

    (Drexel University)

  • Peter P. Chen

    (Louisiana State University)

Abstract

As the popularity and complexity of Internet search engines increase, the design, development and maintenance of large, complex web-based Information Retrieval (WIR) systems become a challenge. The difficulty of designing a WIR system is compounded by information overload triggered from various different information sources. From a standpoint of the search engine users, it is more usable for the WIR to provide a single search point to multiple databases. To tackle this issue, we present the design and implementation of a cross-search component for the CS-Engine (Cross-Search Engine). The CS-Engine allows the user to search heterogeneous, multiple databases with one command. The CS-Engine is also distinguished from meta-search engines in that the CS-Engine does not need to trigger other search engines and translate a query for other search engines. Our performance benchmark tests show that the CS-Engine is scalable and usable. We also compare CS-engine with other search engines such as Google and AltaVista. The CS-Engine was developed with UML and design patterns including: (1) use case diagram, (2) class diagram, (3) package diagram, (4) interaction diagram, (5) Factory pattern, and (6) Strategy patterns. We conclude our paper with technical lessons learned as well as organizational issues encountered during the development phase.

Suggested Citation

  • Min Song & Il-Yeol Song & Peter P. Chen, 2004. "Design and Development of a Cross Search Engine for Multiple Heterogeneous Databases Using UML and Design Patterns," Information Systems Frontiers, Springer, vol. 6(1), pages 77-90, March.
    • Handle: RePEc:spr:infosf:v:6:y:2004:i:1:d:10.1023_b:isfi.0000015876.14848.8c
    DOI: 10.1023/B:ISFI.0000015876.14848.8c
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    Cited by:

    1. Lin-Chih Chen, 2021. "Interactive Topic Search System Based on Topic Cluster Technology," Information Systems Frontiers, Springer, vol. 23(5), pages 1227-1243, September.
    2. Lin-Chih Chen, 0. "Interactive Topic Search System Based on Topic Cluster Technology," Information Systems Frontiers, Springer, vol. 0, pages 1-17.

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