Constraint-based sequential pattern mining: the consideration of recency and compactness
Decision Support Systems
Twain: Two-end association miner with precise frequent exhibition periods
ACM Transactions on Knowledge Discovery from Data (TKDD)
Progressive weighted miner: an efficient method for time-constraint mining
PAKDD'03 Proceedings of the 7th Pacific-Asia conference on Advances in knowledge discovery and data mining
An efficient algorithm for incremental mining of temporal association rules
Data & Knowledge Engineering
A three-scan algorithm to mine high on-shelf utility itemsets
ACIIDS'10 Proceedings of the Second international conference on Intelligent information and database systems: Part II
Discovery of high utility itemsets from on-shelf time periods of products
Expert Systems with Applications: An International Journal
On-shelf utility mining with negative item values
Expert Systems with Applications: An International Journal
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In this paper, we explore a new model of mining generaltemporal association rules from large databases wherethe exhibition periods of the items are allowed to be differentfrom one to another. Note that in this new model,the downward closure property which all prior Apriori-basedalgorithms relied upon to attain good efficiency isno longer valid. As a result, how to efficiently generatecandidate itemsets form large databases has become themajor challenge. To address this issue, we develop an efficientalgorithm, referred to as algorithm SPF (standingfor Segmented Progressive Filter) in this paper. The basicidea behind SPF is to first segment the database into sub-databasesin such a way that items in each sub-databasewill have either the common starting time or the commonending time. Then, for each sub-database, SPF progressivelyfilters candidate 2-itemsets with cumulative filteringthresholds either forward or backward in time. This featureallows SPF of adopting the scan reduction techniqueby generating all candidate k-itemsets (k 2) from candidate2-itemsets directly. The experimental results show thatalgorithm SPF significantly outperforms other schemeswhich are extended from prior methods in terms of the executiontime and scalability.