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Data Mining

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

  1. Intelligent Metasearch Engine for Knowledge Management.

    Eui-Hong (Sam) Han, George Karypis, Doug Mewhort, and Keith Hatchard. 12th Conference of Information and Knowledge Management, pp. 492-495, 2003.

  1. Discovering Frequent Geometric Subgraphs.

    Michihiro Kuramochi and George Karypis. 2nd IEEE Conference on Data Mining (ICDM), pp. 258 - 265, 2002.

  1. SLPMiner: An Algorithm for Finding Frequent Sequential Patterns Using Length Decreasing Support Constraint.

    Masakazu Seno and George Karypis. 2nd IEEE Conference on Data Mining (ICDM), pp. 418-425, 2002.

  1. Evaluation of Hierarchical Clustering Algorithms for Document Datasets.

    Ying Zhao and George Karypis. 11th Conference of Information and Knowledge Management (CIKM), pp. 515-524, 2002.

  1. Using Conjunction of Attribute Values for Classification.

    Mukund Deshpande and George Karypis. 11th Conference of Information and Knowledge Management (CIKM), pp. 356 - 364, 2002.

  1. Automated Approaches for Classifying Structures.

    Mukund Deshpande, Michihiro Kuramochi, and George Karypis. SIGKDD Workshop on Bioinformatics, BIOKDD, 2002.

  1. Evaluation of Techniques for Classifying Biological Sequences.

    Mukund Deshpande and George Karypis. 6th Pacific-Asia Conference on Knowledge Discovery (PAKDD), pp. 417-431, 2002.

  1. Recommender Systems for Large-Scale E-Commerce: Scalable Neighborhood Formation Using Clustering.

    Badrul Sarwar, George Karypis, Joseph Konstan, and John Riedl. 5th International Conference on Computer and Information Technology (ICCIT), 2002.

  1. Incremental SVD-Based Algorithms for Highly Scalable Recommender Systems.

    Badrul Sarwar, George Karypis, Joseph Konstan, and John Riedl. 5th International Conference on Computer and Information Technology (ICCIT), 2002.

  1. Criterion Functions for Document Clustering: Experiments and Analysis.

    Ying Zhao and George Karypis. UMN CS 01-040, 2001.

  1. LPMiner: An Algorithm for Finding Frequent Itemsets Using Length Decreasing Support Constraint.

    Masakazu Seno and George Karypis. 1st IEEE Conference on Data Mining, pp. 505-512, 2001.

  1. Frequent Subgraph Discovery.

    Michihiro Kuramochi and George Karypis. 1st IEEE Conference on Data Mining, pp. 313-320, 2001.