Readings for CMPUT 695

After each student presentation, attending students should fill in the presentation evaluation form and are asked to submit a written evaluation to the instructor (zaiane@cs.ualberta.ca) answering the following questions:
  • What did you like in this presentation?
  • Was the topic clearly presented?
  • Were the slides understandable?
  • What could be done to improve the presentation?
  • Do you have any suggestions for the speaker?
    The evaluations are anonymous in the sense that only the instructor will see your name on your evaluation. The evaluations and comments will be summarized and sent to the presenter.
    Note:--All linked papers are local and in pdf format.
  • Oct 30 [Veena] (presentation file )
    Dynamic Itemset Counting and Implication Rules for Market Basket Data
    http://www-db.stanford.edu/~sergey/dic.ps
    S. Brin, R. Motwani, J. D. Ullman and S.Tsur. SIGMOD'97, pp. 255-264, Tuscon, Arizona, May 1997
  • Oct 30 [Maria] (presentation file )
    Mining Frequent Patterns without Candidate Generation
    ftp://ftp.fas.sfu.ca/pub/cs/han/pdf/sigmod00.pdf
    http://www.acm.org/sigmod/sigmod00/eproceedings/papers/jawei.pdf
    Jiawei Han, Jian Pei, Yiwen Yin, Proc. 2000 ACM-SIGMOD, Dallas, TX, May 2000
  • Nov 1 [Luiza] (presentation file )
    CLOSET: An Efficient Algorithm for Mining Frequent Closed Itemset
    ftp://ftp.fas.sfu.ca/pub/cs/han/pdf/dmkd00.pdf
    J. Pei, J. Han, and R. Mao, Proc. 2000 ACM-SIGMOD Int. Workshop on Data Mining and Knowledge Discovery (DMKD'00), Dallas, TX, May 2000
  • Nov 1 [Bin] (presentation file )
    Mining Recurrent Items in Multimedia with Progressive Resolution Refinement
    http://www.cs.ualberta.ca/~zaiane/postscript/icde00.pdf
    Osmar R. Zaļane, Jiawei Han, Hua Zhu Conf. on Data Engineering (ICDE'2000), pp. 461-470, San Diego, CA, February, 2000
  • Nov 8 [Yue] (presentation file )
    An iterative-improvement approach for the discretization of numeric attributes in Bayesian classifiers.
    http://www.ics.uci.edu/~pazzani/Publications/aniterative.pdf
    M. Pazzani KDD'95, Montreal
  • Nov 8 [Bassem] (presentation file )
    Boosting, Bagging, and C4.5
    http://www.cse.unsw.edu.au/~quinlan/q.aaai96.ps
    J. R. Quinlan AAAI'96, pp 725-730
  • Nov 10 [Darse] (Presentation)
    Efficient and Effective Clustering Method for Spatial Data Mining
    ftp://ftp.fas.sfu.ca/pub/cs/han/kdd/vldb94.ps
    R. Ng and J. Han, Conf. on Very Large Data Bases (VLDB'94), Santiago, Chile, September 1994.
  • Nov 10 [Nathan] (presentation file )
    BIRCH: an efficient data clustering method for very large databases.
    http://www.acm.org/pubs/articles/proceedings/mod/233269/p103-zhang/p103-zhang.pdf
    T. Zhang, R. Ramakrishnan, and M. Livny. SIGMOD'96, pp. 103-114, Montreal, Canada, June 1996.
  • Nov 17 [Xiang] (presentation file )
    CURE: An Efficient Clustering Algorithm for Large Databases
    http://citeseer.nj.nec.com/guha98cure.html
    S. Guha, R. Rastogi, K. Shim SIGMOD'98, Seattle, Washington, 1998
  • Nov 17 [Weinan] (presentation file )
    ROCK: A Clustering Algorithm for Categorical Attributes
    http://citeseer.nj.nec.com/guha99rock.html
    S. Guha, R. Rastogi, K. Shim ICDE'99, Sydney, Australia, 1999
  • Nov 20 [Jeff] (presentation file )
    Chameleon: Hierarchical Clustering Using Dynamic Modeling
    http://www.computer.org/computer/co1999/r8068abs.htm
    http://dlib.computer.org/co/books/co1999/pdf/r8068.pdf
    George Karypis, Eui-Hong (Sam) Han, and Vipin Kumar
  • Nov 20 [Chihoon] (presentation file )
    A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases.
    Click here for the paper
    M. Ester, H.-P. Kriegel, J. Sander, and X. Xu. Conference on Data Mining KDD-96, pp. 226--231, Portland, Oregon, August 1996.
  • Nov 22 [Mufida] (presentation file )
    Spatial Data Mining: Progress and Challenges
    http://db.cs.sfu.ca/GeoMiner/survey/html/survey.html (Also in pdf)
    Krzysztof Koperski, Jiawei Han, Junas Adhikary
  • Nov 22 [Li] (presentation file )
    Automatic Subspace Clustering of High Dimensional Data for Data Mining Applications
    (paper about Clique is here)
    Sigmod 1998
    Rakesh Agrawal, Johannes Gehrke, Dimitrios Gunopulos, Prabhakar Raghavan
  • Nov 24 [Anita] (presentation file )
    Efficient Mining of Partial Periodic Patterns in Time Series Database.
    ftp://ftp.fas.sfu.ca/pub/cs/han/pdf/icde99.pdf
    J. Han, G. Dong, and Y. Yin ICDE'99, pp. 106-115, Sydney, Australia, March 1999
  • Nov 24 [Andrew] (presentation file )
    Mining Segment-Wise Periodic Patterns in Time-Related Databases
    ftp://ftp.fas.sfu.ca/pub/cs/han/pdf/kdd98.pdf
    J. Han, W. Gong, and Y. Yin, Proc. of 1998 Int'l Conf. on Knowledge Discovery and Data Mining (KDD'98) , New York City, NY, Aug. 1998
  • Nov 27 [Alex C.] (presentation file )
    Web Page Categorization and Feature Selection Using Association Rule and Principal Component Clustering.
    http://maya.cs.depaul.edu/~mobasher/papers/webace-wits97.ps
    J. Moore, E. Han, D. Boley, M. Gini, R. Gross, K. Hastings, G. Karypis, V. Kumar, and B. Mobasher WITS'97, December 1997
  • Nov 27 [Ying] (presentation file )
    An Application of Text Mining: Bibliographic Navigator Powered by Extended Association Rules
    http://computer.org/proceedings/hicss/0493/04932/04932009abs.htm
    Minoru Kawahara and Hiroyuki Kawano Kyoto University Proceedings of the 33rd Hawaii International Conference on System Sciences, 1998
  • Nov 29 [Inkyo] (presentation file )
    Semi-Structured Data Extraction and Schema Knowledge Mining
    http://computer.org/proceedings/euromicro/0321/volume2/03212310abs.htm
    Enhong Chen and Xufa Wang Proceedings of the 25th Euromicro Conference (EUROMICRO '99)
  • Nov 29 [Qiang] (presentation file )
    Efficient Data Mining for Path Traversal Patterns
    http://computer.org/tkde/tk1998/k0209abs.htm#TopOfPage
    Ming-Syan Chen, Jong Soo Park, and Philip S. Yu IEEE Transactions on Knowledge and Data Engineering, Vol. 10, No. 2, March/April 1998
  • Dec 1 [Yuan] (presentation file )
    SemQuery: Semantic Clustering and Querying on Heterogeneous Features for Visual data
    http://www.cs.buffalo.edu/pub/WWW/faculty/azhang/psfile/heter.ps
    G. Sheikholeslami, W. Chang, and A. Zhang, in the ACM Multimedia'98, September 12-16, 1998, Bristol, UK.
  • Dec 1 [Alex S.] (presentation file )
    WaveCluster: A multiresolusion clustering approach for very large spatial databases
    http://www.cs.buffalo.edu/pub/WWW/faculty/azhang/psfile/vldb98.ps
    Sheikholeslami, Chatterjee, Zhang VLDB 1998