|Title:||Mining inter-sequence patterns||Authors:||Wang C.-S.
|Keywords:||Data mining;Inter-sequence pattern;Inter-transaction pattern;Sequential pattern||Issue Date:||2009||Journal Volume:||36||Journal Issue:||4||Start page/Pages:||8649-8658||Source:||Expert Systems with Applications||Abstract:||
Sequential pattern and inter-transaction pattern mining have long been important issues in data mining research. The former finds sequential patterns without considering the relationships between transactions in databases, while the latter finds inter-transaction patterns without considering the ordered relationships of items within each transaction. However, if we want to find patterns that cross transactions in a sequence database, called inter-sequence patterns, neither of the above models can perform the task. In this paper, we propose a new data mining model for mining frequent inter-sequence patterns. We design two algorithms, M-Apriori and EISP-Miner, to find such patterns. The former is an Apriori-like algorithm that can mine inter-sequence patterns, but it is not efficient. The latter, a new method that we propose, employs several mechanisms for mining inter-sequence patterns efficiently. Experiments show that EISP-Miner is very efficient and outperforms M-Apriori by several orders of magnitude. ? 2008 Elsevier Ltd. All rights reserved.
|Appears in Collections:||資訊管理學系|
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