| Cartesian contour: a concise representation for a collection of frequent sets |
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International Conference on Knowledge Discovery and Data Mining
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Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
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Paris, France
SESSION: Research track papers
table of contents
Pages 417-426
Year of Publication: 2009
ISBN:978-1-60558-495-9
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Authors
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Ruoming Jin
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Kent State University, Kent, OH, USA
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Yang Xiang
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Kent State University, Kent, OH, USA
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Lin Liu
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Kent State University, Kent, OH, USA
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ABSTRACT
In this paper, we consider a novel scheme referred to as Cartesian contour to concisely represent the collection of frequent itemsets. Different from the existing works, this scheme provides a complete view of these itemsets by covering the entire collection of them. More interestingly, it takes a first step in deriving a generative view of the frequent pattern formulation, i.e., how a small number of patterns interact with each other and produce the complexity of frequent itemsets. We perform a theoretical investigation of the concise representation problem and link it to the biclique set cover problem and prove its NP-hardness. We develop a novel approach utilizing the technique developed in frequent itemset mining, set cover, and max k-cover to approximate the minimal biclique set cover problem. In addition, we consider several heuristic techniques to speedup the construction of Cartesian contour. The detailed experimental study demonstrates the effectiveness and efficiency of our approach.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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