A data mining approach to forming general work breakdown structure

Shan Mi-yuan, She Xiaohua, Ren Bin
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引用次数: 2

Abstract

To meet the development trend of the multi-project operations, this paper describes the concepts of project family and general work breakdown structure (GWBS), and then presents a data mining approach to forming GWBS. Work breakdown structure (WBS) instances are represented by a tree graph, and then we propose a similarity metric between a pair of WBS trees. The results of the pairwise comparisons are used as a distance metric for the following k-medoids clustering algorithm that groups the project WBSs into project families. Each classified cluster represents a project family, and it is expressed by a GWBS. Since the GWBS comes from large amount of historical WBS data, its adaptability and configuration ability are improved effectively, and all of these provide a strong guarantee for enterprises to respond quickly to customer needs.
一种形成一般工作分解结构的数据挖掘方法
为适应多项目运营的发展趋势,提出了项目族和通用工作分解结构(GWBS)的概念,并提出了一种构建通用工作分解结构的数据挖掘方法。工作分解结构(WBS)实例用树状图表示,然后提出了一对WBS树之间的相似度度量。两两比较的结果被用作以下k-medoids聚类算法的距离度量,该算法将项目wbs分组到项目族中。每个分类聚类代表一个项目族,用GWBS表示。由于GWBS来源于大量的历史WBS数据,有效地提高了其适应性和配置能力,为企业快速响应客户需求提供了有力保障。
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