https://scholars.lib.ntu.edu.tw/handle/123456789/415123
Title: | Mining inter-sequence patterns | Authors: | Wang C.-S. Lee A.J.T. |
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. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/415123 | ISSN: | 09574174 | DOI: | 10.1016/j.eswa.2008.10.008 |
Appears in Collections: | 資訊管理學系 |
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