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Goal-oriented sequential pattern for network banking chum analysis
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DOI：10.1016/S0957-4174(03)00073-3.png)
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Abstract
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Discovering sequential patterns is one of the most important task in data mining. In this paper we propose an efficient algorithm, called Goal-oriented sequential pattern. It can provide enterprises warning signs soon before they are losing valuable customers and give them reference for decision making. Experiments comparing Apriori showed that Goal-oriented is more efficient, and performs reasonably well for the rules. (C) 2003 Elsevier Ltd. All rights reserved.
Keywords:
data mining
association rule
sequential pattern
goal-oriented
retention analysis
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