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Exploring Enterprise Knowledge Graphs: A Use Case in Software Engineering

机译:探索企业知识图:软件工程中的用例

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When reusing software architectural knowledge, such as design patterns or design decisions, software architects need support for exploring architectural knowledge collections, e.g., for finding related items. While semantic-based architectural knowledge management tools are limited to supporting lookup-based tasks through faceted search and fall short of enabling exploration, semantic-based exploratory search systems primarily focus on web-scale knowledge graphs without having been adapted to enterprise-scale knowledge graphs (EKG). We investigate how and to what extent exploratory search can be supported on EKGs of architectural knowledge. We propose an approach for building exploratory search systems on EKGs and demonstrate its use within Siemens, which resulted in the STAR system used in practice by 200-300 software architects. We found that the EKG's ontology allows making previously implicit organisational knowledge explicit and this knowledge informs the design of suitable relatedness metrics to support exploration. Yet, the performance of these metrics heavily depends on the characteristics of the EKG's data. Therefore both statistical and user-based evaluations can be used to select the right metric before system implementation.
机译:在重用软件架构知识(例如设计模式或设计决策)时,软件架构师需要支持以探索架构知识集合,例如查找相关项目。虽然基于语义的体系结构知识管理工具仅限于通过多面搜索来支持基于查找的任务,并且无法进行探索,但是基于语义的探索性搜索系统主要专注于Web级知识图,而没有适应企业级知识图(EKG)。我们研究如何在何种程度上在建筑知识的心电图上支持探索性搜索。我们提出了一种在EKG上构建探索性搜索系统的方法,并演示了其在西门子内部的使用,从而使STAR系统在200-300名软件设计师中得到了实际应用。我们发现,EKG的本体可以使以前隐含的组织知识变得明确,并且该知识可以为设计合适的相关性度量提供支持,以支持探索。但是,这些指标的性能在很大程度上取决于EKG数据的特征。因此,统计和基于用户的评估都可以用于在系统实施之前选择正确的指标。

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