CAJ | 학술논문

利用客户关系图可以很清晰地看出企业与客户之间的各类关系,便于企业决策者采取针对性的措施来改善客户关系.该文提出了一种基于改进的FP-Growth算法进行客户关系图提取的方法,通过最小支持度寻找到所有的频繁项集,然后结合最小置信度,筛选出所需要的关联规则来提高算法的效率.本方法已应用于浙江中烟CRM系统,结果证明该改进算法有比较好的效果.
이용객호관계도가이흔청석지간출기업여객호지간적각류관계,편우기업결책자채취침대성적조시래개선객호관계.해문제출료일충기우개진적FP-Growth산법진행객호관계도제취적방법,통과최소지지도심조도소유적빈번항집,연후결합최소치신도,사선출소수요적관련규칙래제고산법적효솔.본방법이응용우절강중연CRM계통,결과증명해개진산법유비교호적효과.
Customer relationships can be clearly seen in customer relationship graph, thus business decision-makers can take spe-cific measures to facilitate customer relationships. This paper presents an improved algorithm based on FP-Growth algorithm to ex-tract customer relationship graph. We find all frequent itemsets through minimum support, then filter out the desired association rules integrated with the minimum confidence, which can improve the efficiency of the algorithm considerably. This method has been applied to Zhejiang Tobacco CRM system, and the results show that the improved algorithm is very effective.