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Courses in winter term 2008/2009 / Master-Seminar Clustering / Script:
Abstract
Script

Note on Seminar Paper :

  • Due four weeks after end of term
  • 30 pages at most,
  • 3 hard copies(printed) and 1 soft copy (CD).


    • Note on Grades:
  • Marks will be based on presentation (including answers to questions), seminar paper, and general participation (e.g., asking questions),
  • bonuses for own experiments or implementations. If any, please also include in the CD.

    • Readings:

    0. Introduction
    A Tutorial on Clustering.
    (http://home.dei.polimi.it/matteucc/Clustering/tutorial_html/)

    1. Efficient clustering algorithms
    ZHANG, T., RAMAKRISHNAN, R., AND LIVNY, M. 1996. BIRCH: An efficient data clustering method for very large databases. SIGMOD Rec. 25, 2, 103–114.
    (http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.17.2504&rep=rep1&type=pdf)

    2. Clustering categorical data
    GUHA, S., RASTOGI, R., SHIM, K. 1999. ROCK: A Robust Clustering Algorithm for Categorical Attributes. In Proceedings of the 15th ICDE Conf.
    (http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.17.8558&rep=rep1&type=pdf)

    3. Evaluation of clustering results
    HALKIDI, M., BATISTAKIS, Y., VAZIRGIANNIS, M. Cluster Validity Methods: Part I & II", SIGMOD Rec, June 2002
    ( http://www.db-net.aueb.gr/index.php/corporate/content/download/197/629/file/HBV_SIGREC02(I).pdf and http://www.db-net.aueb.gr/index.php/corporate/content/download/198/636/file/HBV_SIGREC02(II).pdf )

    4. Clustering in biology
    MADEIRA, S.C. OLIVEIRA, A.L. Biclustering algorithms for biological data analysis: a survey. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 1(1), 24-45.
    (http://www.inesc-id.pt/ficheiros/publicacoes/1281.pdf)

    5. Clustering text databases
    BEIL, F., ESTER, M., XU, X. 2002. Frequent Term-Based Text Clustering. In Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
    (http://www.cs.sfu.ca/~ester/papers/KDD02.Clustering.final.pdf)

    6. Clustering WWW pages
    WULFEKUHLER, M. AND PUNCH, W. 1997. Finding salient features for personal web page categories. In Proceedings of the Sixth International Conference on the World Wide Web.
    (http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.50.3545&rep=rep1&type=pdf)

    7. Clustering book collections
    MURTY, M. N. AND JAIN, A. K. 1995. Knowledge-based clustering scheme for collection management and retrieval of library books. Pattern Recogn. 28, 949–964.
    (http://www.citeulike.org/user/jronallo/article/2792194)

    8. Clustering satellite images
    FABER, V., HOCHBERG, J. C., KELLY, P. M., THOMAS, T. R., AND WHITE, J. M. 1994. Concept extraction: A data-mining technique. Los Alamos Science 22, 122–149.
    (http://library.lanl.gov/cgi-bin/getfile?00412966.pdf)