id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_o5pckqbnsfdtndk4vlsk5e43ge	D Chiang	Goal-oriented sequential pattern for network banking churn analysis	2003	10	.pdf	application/pdf	5744	502	69	Discovering sequential patterns is one of the most important task in data mining. Keywords: Data mining; Association rule; Sequential pattern; Goal-oriented; Retention analysis customers can be generated by sequential patterns. association rules by utilizing the large itemset. The sequential patterns originate the association rules mining sequential patterns are Apriori algorithm (Agrawal sequential pattern: Setting large itemset and establishing sequential pattern rules by large itemset. to generate sequential pattern rule from the large itemset. The customer sequence is ordered by increasing transaction time. original items, we can get our mining sequence pattern large itemset to conclude sequential patterns rules. The customer sequence is a list of transactions ordered by The customer sequence is ordered by decreasing transaction time. efficiency of the Goal-oriented sequential patterns algorithm. by the Goal-oriented sequential patterns focus on the rules After we use Goal-oriented sequential patterns algorithm to process the customer loss analysis, the rule of loss	./cache/work_o5pckqbnsfdtndk4vlsk5e43ge.pdf	./txt/work_o5pckqbnsfdtndk4vlsk5e43ge.txt