A data mining approach to forming general work breakdown structure

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.