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A New Efficient Clustering Algorithm for Organizing Dynamic Data Collection

  • Kwangcheol Shin
  • Sangyong Han
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2945)

Abstract

We deal with dynamic information organization for more efficient Internet browsing. As the appropriate algorithm for this purpose, we propose modified ART (artificial resonance theory) algorithm, which functions similarly with the dynamic Star-clustering algorithm but performs a more efficient time complexity of O(nk), (kn) instead of O(n 2 log 2 n) found in the dynamic Star-clustering algorithm. In order to see how fast the proposed algorithm is in producing clusters for organizing information, the algorithm is tested on CLASSIC3 in comparison with the dynamic Star-clustering algorithm.

Keywords

Input Pattern Cosine Similarity Matching Function Information Organization Suggested Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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    Montes-y-Gomez, M., Lopez-Lopez, A., Gelbukh, A.: Information Retrieval with Conceptual Graph Matching. In: Ibrahim, M., Küng, J., Revell, N. (eds.) DEXA 2000. LNCS, vol. 1873, pp. 312–321. Springer, Heidelberg (2000)CrossRefGoogle Scholar
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    Aslam, J., Pelekhov, K., Rus, D.: A Practical Clustering Algorithm for Static and Dyamic Information Organization. In: Proceedings of the 1999 Symposium on Discrete Algorithms, Baltimore, MD (1999)Google Scholar
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    Carpenter, G.A., Grossberg, S., Rosen, D.B.: Fuzzy ART: An Adaptive Resonance Algorithm for Rapid, Stable Classification of Analog Patterns. In: Proceedings of 1991 International Conference Neural Networks, vol. II (1991)Google Scholar
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    Dhillon, I.S., Modha, D.S.: Concept Decomposition for Large Sparse Text Data using Clustering. Technical Report RJ 10147(9502), IBM Almaden Research Center (1999)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Kwangcheol Shin
    • 1
  • Sangyong Han
    • 1
  1. 1.School of Computer Science and EngineeringChung-Ang Univ.SeoulKorea

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