Goal-oriented sequential pattern for network banking chum analysis
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.
goal-oriented sequential pattern data mining association rule retention analysis