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The Research about the Application of Data Mining Technology Based on SLIG in the CRM

机译:基于CRM中纤维的数据挖掘技术应用研究

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First, this paper introduces Relation Regulation in data mining, then an efficient algorithm SLIG ( Single-Level Large Itemsets Generation) based on relation theory and "AND" operation on recognizable vectors was proposed. SLIG transforms the production process of  frequent itemset  to  the vector calculation process with relationship matrix but only needs to scan the database once. We optimize the algorithm farther, and acquire favorable results. According to this algorithm, combining CRM-instance in the insurance company, we present a detailed  process for the solution and analysis of instance, by that we elicit an important conclusion that can bring competition and profit for the company, and also it is a credible gist for reducing risk, at last we analyze the performance among the algorithm of SLIG,  SLIG(optimized SLIG) and Apriori.
机译:首先,本文介绍了数据挖掘的关系规则,提出了基于关系理论的有效算法诸如识别载体的“和”操作的高效算法幻灯片(单级大项集)。 SLIG将频繁项目集的生产过程转换为具有关系矩阵的向量计算过程,但只需要扫描数据库一次。我们优化算法进一步,并获得有利的结果。根据该算法,在保险公司中组合CRM-实例,我们向实例提供了一个详细的解决方案,并通过我们引起了一个重要的结论,可以为本公司带来竞争和利润,也是可靠的为了降低风险的主旨,最后我们分析了Slig,Slig(优化Slig)和Apriori算法之间的性能。

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