应用Apriori算法和K-Means算法确定潜在专家

Rini Sovia, Sarjon Defit, Noor Fatimah
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引用次数: 0

摘要

专家是具有特殊专业知识的人,他们根据自己的专业知识提供服务。公司有专业的项目处理专家,这些项目将为公司的发展而实施。专家素质在公司的重要性可以提高人力资源的质量。Apriori算法是一种数据挖掘方法,其目的是查找基于正在执行的项目的关联模式,以便经常用于处理项目的专家能够识别这些模式。此外,需要一种数据挖掘方法来使用K-means算法对专家进行分类。这项研究结合了Apriori和K-means算法,根据专家处理项目的方式对他们进行分组。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Determination Potential Experts by Application The Apriori Algorithm and the K-Means Algorithm
Experts are people who have special expertise who provide services based on their expertise. The company has experts in handling projects that will be carried out for the progress of the company. The importance of the quality of experts in the company can improve the quality of human resources. The Apriori algorithm is a data mining method that has the aim of looking for association patterns based on the project being carried out so that they can be identified by experts who are often used in handling projects. Furthermore, a data mining approach is needed to classify experts with the K-means algorithm used. This study combines the Apriori and K-means algorithms, by grouping experts based on the handling of the project they are working on.
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