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An Efficient Algorithm for Dense Regions Discovery from Large-Scale Data Streams

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Advances in Knowledge Discovery and Data Mining (PAKDD 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3056))

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Abstract

We introduce the notion of dense region as distinct and meaningful patterns from given data. Efficient and effective algorithms for identifying such regions are presented. Next, we discuss extensions of the algorithms for handling data streams. Finally, experiments on large-scale data streams such as clickstreams are given which confirm that the usefulness of our algorithms.

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References

  1. Huang, J., Ng, M., Ching, W., Ng, J., Cheung, D.: A cube model and cluster analysis for web access sessions. In: Kohavi, R., Masand, B., Spiliopoulou, M., Srivastava, J. (eds.) WebKDD 2001. LNCS (LNAI), vol. 2356, p. 48. Springer, Heidelberg (2002)

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  2. Wu, E.H., Ng, M.K., Huang, J.Z.: On improving website connectivity by using web-log data streams. In: Lee, Y., Li, J., Whang, K.-Y., Lee, D. (eds.) DASFAA 2004. LNCS, vol. 2973, pp. 352–364. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  3. Wu, E.H., Ng, M.K.: A graph-based optimization algorithm for Website topology using interesting association rules. In: Proc. of PAKDD 2003, Seoul, Korea (2003)

    Google Scholar 

  4. Yang, C., Fayyad, U., Bradley, P.S.: Efficient discovery of error-tolerant frequent itemsets in high dimensions. In: Proc. of ACM SIGKDD Intl. Conf. on Knowledge Discovery and Data Mining: San Francisco, California, pp. 194–203 (2001)

    Google Scholar 

  5. Yip, A.M., Wu, E.H., Ng, M.K., Chan, T.F.: An efficient algorithm for dense regions discovery from large-scale data streams (extended version), UCLA CAM Reports 03-76, Math. Dept., University of California, Los Angeles, CA (2003)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Mathematics, University of California, 405 Hilgard Avenue, Los Angeles, CA, 90095-1555, USA

    Andy M. Yip & Tony F. Chan

  2. Department of Mathematics, The University of Hong Kong, Pokfulam Road, Hong Kong

    Edmond H. Wu & Michael K. Ng

Authors
  1. Andy M. Yip
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  2. Edmond H. Wu
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  3. Michael K. Ng
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  4. Tony F. Chan
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Editor information

Editors and Affiliations

  1. School of Engineering and Information Technology, Deakin University, VIC 3125, Australia

    Honghua Dai

  2. University of Illinois at Urbana-Champaign, 61801, Urbana, IL, USA

    Ramakrishnan Srikant

  3. Faculty of Engineering and Information Technology, Centre for Quantum Computation and Intelligent Systems, and Australian ACS National Committee for Artificial Intelligence, University of Technology, Sydney, Australia

    Chengqi Zhang

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© 2004 Springer-Verlag Berlin Heidelberg

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Yip, A.M., Wu, E.H., Ng, M.K., Chan, T.F. (2004). An Efficient Algorithm for Dense Regions Discovery from Large-Scale Data Streams. In: Dai, H., Srikant, R., Zhang, C. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2004. Lecture Notes in Computer Science(), vol 3056. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24775-3_14

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  • DOI: https://doi.org/10.1007/978-3-540-24775-3_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22064-0

  • Online ISBN: 978-3-540-24775-3

  • eBook Packages: Springer Book Archive

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