Network analysis is found to be effective for mining various aspects from technological and scientific literature. Path analysis, a major tool in the network analysis trio, consists of two crucial steps-weight assignment and search method. An innovative search scheme namely, key-route search method is found to be capable of retrieving multiple paths. Recently, a framework that explored the power of combined networks or NoNs (Network of networks) for interdisciplinarity assessment was proposed. In this work, a framework that utilizes the strength of NoNs and the integrated approach to path analysis is developed for mining the interdisciplinary trajectories in techno-scientific literature. Among the two major weight assignment schemes such as SPC and FV gradient schemes, FV gradient is found to better leverage key-route search scheme in mining multiple evolutionary trajectories with interdisciplinary interactions. This framework can serve as a handy tool for a multitude of beneficiaries including policy makers.

中文翻译：

---

使用多路径分析挖掘跨学科轨迹

发现网络分析对于从技术和科学文献中挖掘各个方面是有效的。路径分析是网络分析三重奏中的主要工具，由两个关键步骤组成——权重分配和搜索方法。一种创新的搜索方案，即关键路径搜索方法被发现能够检索多条路径。最近，提出了一个探索组合网络或 NoN（网络网络）用于跨学科评估的能力的框架。在这项工作中，开发了一个利用 NoN 的优势和综合路径分析方法的框架，用于挖掘技术科学文献中的跨学科轨迹。在 SPC 和 FV 梯度方案等两种主要的权重分配方案中，发现 FV 梯度可以更好地利用关键路径搜索方案来挖掘具有跨学科交互的多个进化轨迹。该框架可以作为包括政策制定者在内的众多受益者的便捷工具。