Lessons learned from completed projects are valuable resources for planning of new projects. A quantitative similarity measurement between construction projects can improve knowledge reuse practices. The information and documents of a similar past project can be retrieved to resolve the challenges in a new project. This paper introduces a novel method for measuring the similarity of construction projects based on semantic comparison of their work breakdown structure (WBS). WBS of a project should theoretically encompass a hierarchical decomposition of the total scope of project’s works, thus it could be used as an appropriate representative of the projects. The proposed method measures the semantic similarity between WBS of projects by means of natural language processing techniques. This method was implemented based on three metrics: node, structural, and total similarity. Each of these metrics calculate a quantitative similarity score between 0 and 1. The method was assessed using fifteen test samples with promising results in compliance with similarity properties. In addition, precision and recall of the method were evaluated in retrieving similar past projects. The results illustrate that the structural similarity slightly outperforms the other metrics.

从完成的项目中学到的经验教训对于计划新项目是宝贵的资源。建设项目之间的定量相似性度量可以改善知识重用实践。可以检索过去类似项目的信息和文档，以解决新项目中的挑战。本文介绍了一种基于工作分解结构（WBS）语义比较的测量工程项目相似性的新方法。理论上，项目的WBS应该包含项目作品总范围的层次分解，因此可以用作项目的适当代表。所提出的方法通过自然语言处理技术来测量项目的WBS之间的语义相似度。该方法是基于以下三个指标实现的：节点，结构上和总体上相似。这些指标中的每一个都会计算0到1之间的定量相似性评分。使用15个测试样品对方法进行了评估，结果令人满意，符合相似性。此外，在检索类似的过去项目时，还对该方法的精度和召回率进行了评估。结果表明，结构相似性略胜于其他指标。