论文标题
通过数据挖掘技术检测非正式组织
Detecting Informal Organization Through Data Mining Techniques
论文作者
论文摘要
人力资源管理中的主要主题之一是组织中非正式组织的主题,即认识和管理此类非正式组织在组织中起着重要作用。一些经理正在试图认识到非正式组织之间的关系,并成为他们可以协助正式组织发展的成员。认识非正式组织的方法很复杂,偶尔甚至是不可能的。这项研究旨在提供一种使用数据挖掘技术识别此类组织的方法。这项研究对人力资源的指标进行了分类,这些索引影响了非正式组织的创建,包括组织员工的个人,社会和工作特征。然后,问卷是在员工中设计和分发的。从获得的数据创建数据库。这项研究中的应用数据挖掘技术是因子分析,由K均值聚集,决策树的分类以及GRI算法的最终关联规则挖掘。最后,提出了一个模型,该模型适用于识别人们之间的类似特征,以最佳地识别非正式组织和使用此信息。
One of the main topics in human resources management is the subject of informal organizations in the organization such that recognizing and managing such informal organizations play an important role in the organizations. Some managers are trying to recognize the relations between informal organizations and being a member of them by which they could assist the formal organization development. Methods of recognizing informal organizations are complicated and occasionally even impossible. This study aims to provide a method for recognizing such organizations using data mining techniques. This study classifies indices of human resources influencing the creation of informal organizations, including individual, social, and work characteristics of an organizations employees. Then, a questionnaire was designed and distributed among employees. A database was created from obtained data. Applied data mining techniques in this study are factor analysis, clustering by K-means, classification by decision trees, and finally association rule mining by GRI algorithm. At the end, a model is presented that is applicable for recognizing the similar characteristics between people for optimal recognition of informal organizations and usage of this information.