Exploratory mining and pruning optimizations of constrained associations rules
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Mining Frequent Patterns without Candidate Generation: A Frequent-Pattern Tree Approach
Data Mining and Knowledge Discovery
TFP: An Efficient Algorithm for Mining Top-K Frequent Closed Itemsets
IEEE Transactions on Knowledge and Data Engineering
MAFIA: A Maximal Frequent Itemset Algorithm
IEEE Transactions on Knowledge and Data Engineering
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Selecting faculty members to form a mission committee and simultaneously scheduling the corresponding committee meetings is a tough decision problem frequently encountered in every academic department. In this paper, we present a formal model of the problem. We also present an approach showing that, with simple database construction, the problem can be transformed into a constrained itemset mining problem, which is an important branch of frequent itemset mining. Thus, the problem can be exactly solved by techniques for constrained itemset mining. For high efficiency, we provide a method to convert some problem constraint into an anti-monotone constraint, which can be easily embedded into the framework of frequent itemset mining and is considered very effective for search space pruning. Experiments were performed and the results show that our approach offers very high performance.