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Data Mining

Here is a list of publications that are related to our data mining research.

  1. Topic-Driven Clustering for Document Datasets.

    Ying Zhao and George Karypis. SIAM International Conference on Data Mining, pp. 358-369, 2005.

  1. Profile Based Direct Kernels for Remote Homology Detection and Fold Recognition.

    Huzefa Rangwala and George Karypis. Bioinformatics, Vol. 31, No. 23, pp. 4239 - 4247, 2005.

  1. Data Clustering in Life Sciences.

    Ying Zhao and George Karypis. Molecular Biotechnology, 31(1), pp. 55--80, 2005.

  1. Gene Classification using Expression Profiles: A Feasibility Study.

    Michihiro Kuramochi and George Karypis. International Journal on Artificial Intelligence Tools. Vol. 14, No. 4, pp. 641 - 660, 2005.

  1. Frequent Sub-structure Based Approaches for Classifying Chemical Compounds.

    Mukund Deshpande, Michihiro Kuramochi, Nikil Wale, and George Karypis. IEEE Trans. Knowl. Data Eng. 17(8): 1036-1050, 2005.

  1. Influence in Ratings-Based Recommender Systems: An Algorithm-Independent Approach.

    Al Mamunur Rashid, George Karypis, and John Riedl. SIAM International conference on Data Mining, 2005.

  1. Feature-Based Recommendation System.

    Eui-Hong (Sam) Han and George Karypis. Proceedings of the 14th Conference of Information and Knowledge Management (CIKM), pp. 446 - 452, 2005.

  1. Selective Markov Models for Predicting Web-Page Accesses.

    Mukund Deshpande and George Karypis. ACM Transactions on Internet Technology, Vol. 4, Issue 2, pp. 163 - 184, 2004.

  1. Macromolecule Mass Spectrometry: Citation Mining of User Documents.

    R. N. Kostoff, C. D. Bedford, J. Antonio del Rio, H. D. Cortes, and G. Karypis. Journal of the American Society for Mass Spectrometry, Vol. 15, No. 3, pp. 281 - 287, 2004.

  1. Empirical and Theoretical Comparisons of Selected Criterion Functions for Document Clustering.

    Ying Zhao and George Karypis. Machine Learning, 55, pp. 311-331, 2004.

  1. Soft Clustering Criterion Functions for Partitional Document Clustering.

    Ying Zhao and George Karypis. 13th Conference of Information and Knowledge Management (CIKM), pp. 246-247, 2004.

  1. GREW: A Scalable Frequent Subgraph Discovery Algorithm.

    Michihiro Kuramochi and George Karypis. 4th IEEE Conference on Data Mining (ICDM), pp. 439-442, 2004.