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Related Experiment Videos

Mining multilevel and location-aware service patterns in mobile web environments.

Shin-Mu Tseng, Ching-Fu Tsui

    IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society
    |December 29, 2004
    PubMed
    Summary

    This study introduces a novel two-dimensional multilevel (2-DML) association rules mining method for mobile web environments. It efficiently uncovers hierarchical service patterns, enhancing location-based and personalized services.

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    Area of Science:

    • Data Mining
    • Mobile Computing
    • Service Science

    Background:

    • Mobile web environments present complex, hierarchical structures for locations and services.
    • Existing data mining methods struggle to efficiently process these multilevel relationships.

    Purpose of the Study:

    • To develop an efficient data mining method for uncovering multilevel, location-aware associated service patterns.
    • To address the challenge of hierarchical structures in mobile service requests.

    Main Methods:

    • Proposed a novel two-dimensional multilevel (2-DML) association rules mining technique.
    • Developed variations of the 2-DML method focusing on execution and memory efficiency.

    Main Results:

    • The 2-DML method efficiently discovers associated service request patterns considering multilevel location and service hierarchies.

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  • Empirical evaluations demonstrate good performance in efficiency and scalability across various system conditions.

    • Conclusions:

    • The 2-DML method is the first to address multilevel and location-aware service pattern mining in mobile environments.
    • Discovered patterns are valuable for real-world applications like personalized and location-based services.