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Related Experiment Videos

Stochastic clustering for organizing distributed information sources.

Mei-Ling Shyu1, Shu-Ching Chen, Stuart H Rubin

  • 1Department of Electrical and Computer Engineering, University of Miami, Coral Gables, FL 33124, USA. shyu@miami.edu

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society
|October 27, 2004
PubMed
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A new Markov model mediator (MMM) clusters information sources by data access behavior. This improves information retrieval efficiency and system response times in complex data environments.

Area of Science:

  • Computer Science
  • Information Science
  • Data Management

Background:

  • The proliferation of data sources and increasing application complexity necessitate efficient information navigation and retrieval tools.
  • Distributed environments often require queries to access multiple information sources, posing challenges for performance and usability.
  • Clustering offers a structural approach to organize vast information sources for effective browsing and searching.

Purpose of the Study:

  • To introduce a novel stochastically-based clustering mechanism, the Markov model mediator (MMM).
  • To group information sources based on similarities in data access behavior.
  • To enhance system response time, query performance, and decision support in distributed information environments.

Main Methods:

Related Experiment Videos

  • Developed a clustering mechanism named the Markov model mediator (MMM).
  • Grouped information sources into clusters based on shared data access patterns.
  • Evaluated the MMM's effectiveness through empirical studies on real databases.

    • Main Results:

    • The MMM successfully grouped information sources with similar data access behaviors.
    • Clusters formed by the MMM demonstrated superior organization compared to other clustering methods.
    • Empirical results validated the MMM's effectiveness in improving information retrieval.

    Conclusions:

    • The Markov model mediator (MMM) provides an effective method for clustering information sources.
    • This approach significantly enhances system performance and decision support capabilities.
    • The MMM offers a valuable tool for managing and retrieving information in large-scale distributed systems.