Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Finding interesting rules from large sets of discovered association rules
CIKM '94 Proceedings of the third international conference on Information and knowledge management
Data mining, hypergraph transversals, and machine learning (extended abstract)
PODS '97 Proceedings of the sixteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Automatic subspace clustering of high dimensional data for data mining applications
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Concise Representation of Frequent Patterns Based on Generalized Disjunction-Free Generators
PAKDD '02 Proceedings of the 6th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
Graph indexing: a frequent structure-based approach
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Approximating a collection of frequent sets
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Summarizing itemset patterns: a profile-based approach
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Mining compressed frequent-pattern sets
VLDB '05 Proceedings of the 31st international conference on Very large data bases
A randomized polynomial-time simplex algorithm for linear programming
Proceedings of the thirty-eighth annual ACM symposium on Theory of computing
Summarizing itemset patterns using probabilistic models
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
\delta-Tolerance Closed Frequent Itemsets
ICDM '06 Proceedings of the Sixth International Conference on Data Mining
Data Mining and Knowledge Discovery
Effective and efficient itemset pattern summarization: regression-based approaches
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Direct Discriminative Pattern Mining for Effective Classification
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
CloseViz: visualizing useful patterns
Proceedings of the ACM SIGKDD Workshop on Useful Patterns
Block interaction: a generative summarization scheme for frequent patterns
Proceedings of the ACM SIGKDD Workshop on Useful Patterns
Fast mining erasable itemsets using NC_sets
Expert Systems with Applications: An International Journal
Finding minimum representative pattern sets
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Summarizing probabilistic frequent patterns: a fast approach
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
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This paper tackles the problem of summarizing frequent itemsets. We observe that previous notions of summaries cannot be directly used for analyzing frequent itemsets. In order to be used for analysis, one requirement is that the analysts should be able to browse all frequent itemsets by only having the summary. For this purpose, we propose to build the summary based upon a novel formulation, conditional profile (or c-profile). Several features of our proposed summary are: (1) each profile in the summary can be analyzed independently, (2) it provides error guarantee (ε-adequate), and (3) it produces no false positives or false negatives. Having the formulation, the next challenge is to produce the most concise summary which satisfies the requirement. In this paper, we also designed an algorithm which is both effective and efficient for this task. The quality of our approach is justified by extensive experiments. The implementations for the algorithms are available from www.cais.ntu.edu.sg/~vivek/pubs/cprofile09.