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Abstract: Unexpected rules are interesting because they are either previously unknown or deviate from what prior user knowledge would suggest. In this paper, we study three important issues that have been previously ignored in mining unexpected rules. First, the unexpectedness of a rule depends on how the user prefers to apply the prior knowledge to a given scenario, in addition to the knowledge itself. Second, the prior knowledge should be considered right from the start to focus the search on... (Update)
Active bibliography (related documents): More All
0.5: Discovery of Multiple-Level Association Rules from Large Databases - Han, Fu (1995) (Correct)
0.2: Pushing Aggregate Constraints by Divide-and-Approximate - Wang, Jiang, Yu, Dong, Han (2003) (Correct)
0.2: Pushing Support Constraints Into Association Rules Mining - Wang, He, Han (Correct)
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BibTeX entry: (Update)
@misc{ wang-mining,
author = "Ke Wang and Yuelong Jiang and Laks V.S. Lakshmanan",
title = "Mining Unexpected Rules by Pushing User Dynamics",
url = "citeseer.ist.psu.edu/article/wang03mining.html" }
Citations (may not include all citations):910 Fast algorithm for mining association rules - Agrawal, Srikant - 1994
161 Exploratory mining and pruning optimizations of constrained .. - Ng, Lakshmanan et al. - 1998
156 Beyond market baskets: Generalizing association rules to cor.. - Brin, Motwani et al. - 1997
137 Finding interesting rules from large sets of discovered asso.. - Klemettinen, Mannila et al. - 1994
121 Mining association rules with item constraints - Srikant, Vu et al. - 1997
85 Constraint-based rule mining in large (context) - Bayardo, Agrawal et al. - 1999
80 What makes patterns interesting in knowledge discovery syste.. - Silberschatz, Tuzhilin - 1996
77 Bottom-up computation of sparse and iceberg cubes - Beyer, Ramakrishnan - 1999
73 Mining the most interesting rules (context) - Bayardo, Agrawal - 1999
56 Generating non-redundant association rules - Zaki - 2000
37 Using general impressions to analyze discovered classificati.. - Liu, Hsu et al. - 1997
30 Post-analysis of learned rules - Liu, Hsu - 1996
15 Interestingness measures for association patterns: A perspec.. - Tan, Kumar - 2000
14 Unexpectedness as a measure of interestingness in knowledge .. - Padmanabhan, Tuzhilin - 1998
12 Small is beautiful: Discovering the minimal set of unexpecte.. - Padmanabhan, Tuzhilin - 2000
5 Pushing support constraints into frequent itemset mining (context) - Wang, He et al. - 2000
2 The interestingness of deviations (context) - Piatesky-Shapiro, Matheus - 1994
1 On subjective measures of interestingnessin in knowledge dis.. (context) - Silberschatz, Tuzhilin - 1995
1 Interestingnes via what is not interesting (context) - Sahar - 1999
1 Pushing aggregate constraints by divide-and-approximate - Wang, Jiang et al. - 2003
1 analysis and presentation of strong rules (context) - Piatesky-Shapiro - 1991
1 A belief-drievn method for discovering unexpected patterns (context) - Padmanabhan, Tuzhilin - 1998
http://kdd.ics.uci.edu/databases/kddcup98/kddcup98.html
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Growing Decision Trees On Support-Less Association Rules - Wang, Zhou, He (2000) (Correct)
Mining Frequent Itemsets Using Support Constraints - Wang, He, Han (2000) (Correct)
Hierarchical Classification of Real Life Documents - Ke Wang Senqiang (2001) (Correct)
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