Database Reference
In-Depth Information
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93. S. Madeira, and A. Oliveira. Biclustering Algorithms for Biological Data Analysis; A Survey,
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94. H. Mannila, and H. Toivonen. Discovering Generalized Episodes using Minimal Occurrences,
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97. H. J. Miller, and J. Han. Geographic Data Mining and Knowledge Discovery.
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99. S. Mitra, and H. Banka. Multi-objective Evolutionary Biclustering of Gene Expression Data,
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100. B. Mobasher, R. Cooley, and J. Srivastava. Automatic personalization based on Web usage
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101. B. Mobasher, H. Dai, T. Luo, and M. Nakagawa. Effective personalization based on associ-
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102. A. Nanopoulos, and Y. Manolopoulos. Finding generalized path patterns for web log data
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103. A. Nanopoulos, and Y. Manolopoulos. Efficient similarity search for market basket data,
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104. F. Pan, G. Cong, A. Tung, J. Yang, and M. Zaki. CARPENTER: Finding closed patterns in
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105. F Pan, A. K. H. Tung, G. Cong, X. Xu. COBBLER: Combining column and Row Enumeration
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106. L. Parsons, E. Haque, and H. Liu. Subspace Clustering for High Dimensional Data: A Review,
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107. J. Pei, and J. Han. Can we push more constraints into frequent pattern mining?
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108. J. Pei, J. Han, B. Mortazavi-Asl and H. Zhu. Mining access patterns efficiently from web
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109. J. Pei, J. Han, and L. V. S. Lakshmanan. Mining Frequent Patterns with Convertible Constraints
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110. J. Punin, M. Krishnamoorthy, M. Zaki. Web usage mining: languages and algorithms.
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111. I. Rigoutsos, and A. Floratos. Combinatorial Pattern Discovery in Biological Sequences: The
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114. P. Shenoy, J. Haritsa, S. Sudarshan, G. Bhalotia, M. Bawa, D. Shah. Turbo-charging Vertical
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115. A. Siebes, J. Vreeken, and M. van Leeuwen. Itemsets than Compress,
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