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Conceptual Object Grouping for Multimedia Document Management

Lee, Chong-Deuk    (Division of Applied System Engineering, Chonbuk National Univ.   ); Jeong, Taeg-Won    (Division of Applied System Engineering, Chonbuk National Univ.  );
  • 초록

    Increase of multimedia information in Web requires a new method to manage and service multimedia documents efficiently. This paper proposes a conceptual object grouping method by fuzzy filtering, which is automatically constituted based on increase of multimedia documents. The proposed method composes subsumption relations between conceptual objects automatically using fuzzy filtering of the document objects that are extracted from domains. Grouping of such conceptual objects is regarded as subsumption relation which is decided by $\mu$ -cut. This paper proposes $\mu$ -cut, FAS(Fuzzy Average Similarity) and DSR(Direct Subsumption Relation) to decide fuzzy filtering, which groups related document objects easily. This paper used about 1,000 conceptual objects in the performance test of the proposed method. The simulation result showed that the proposed method had better retrieval performance than those for OGM(Optimistic Genealogy Method) and BGM(Balanced Genealogy Method).


  • 주제어

    fuzzy filtering .   $\mu$-cut .   FAS .   DSR.  

  • 참고문헌 (10)

    1. Filip Perich, Anupam Joshi, Senior Member, IEEE, Timothy Finin, and Yelena Yesha, Senior Member, IEEE, "On Data Management in Pervasive Computing Environment," IEEE Trans. on Knowledge and Data Engineering, vol. 16, no. 5, pp. 621-633, 2004 
    2. Yinghui Yang and Balaji Padmanabhan, "GHIC: A Hierarchical Pattern-Based Clustering Algorithm for Grouping Web Transaction," IEEE Trans. on Knowledge and Data Engineering, vol. 17, no. 9, pp. 1300-1304, 2005 
    3. K. Bohms, and T. C. Rakow, "Metadata for Multimedia Documents," SIGMOD Record, vol. 23, no. 4, pp. 21-26, 1994 
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    6. Prasanna Ganesan, Hector Garcia-Molina, and Jennifer Widom, "Exploiting Hierarchical Domain Structure to Compute Similarity," ACM Trans. on Information Systems, vol. 21, pp. c, 2003 
    7. Laszlo T. Koczy and T. Geodeon, "Information Retrieval by Fuzzy Relations and Hierarchical Co-occurrence," Part I. TR97-01, Dept. of Info. Eng., School of Com. Sci. & Eng., UNSW, pp. 1-18, 1997 
    8. Elina Megalou, and Thanasis Hadzilacos, "Semantic Abstractions in the Multimedia Domain," IEEE Trans. on Knowledge and Data Engineering, vol. 15, no. 1, pp. 136-160, 2003 
    9. Guojun Lu, "Techniques and Data Structure for Efficient Multimedia Retrieval Based on Similarity," IEEE Trans. on Multimedia, vol. 4, no. 3, pp. 372-384, 2002 
    10. Hisham AI-Mubaid and Syed A. Umair, "A new text Categorization Technique Using Distributional Clustering and Learning Logic,' IEEE Trans. on Knowledge and Data Engineering, vol. 18, no. 9, pp. 1156-1165, 2006 

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