Abstract: Traditional document organization methods are inadequate to address the evolving trends of standard digitization. It is essential to uncover the multi-granularity knowledge units and their semantic associations within standard documents, to explore novel organizational methods that can efficiently utilize standard knowledge, and to provide references for optimizing standard provision. From the perspective of knowledge association, this study proposed a multi-granularity, semantically-rich, and universal knowledge organization method for standard documents. Firstly, based on the Knowledge Granularity Theory, knowledge partitioning and description at multiple granularities are carried out according to the knowledge content and requirement characteristics of standard documents. Secondly, the semantic association patterns and types among multi-granularity knowledge units are recognized and discovered from aspects such as knowledge hierarchy, document features, text logic, and spatiotemporal evolution. Finally, the method of ontology construction is employed to achieve multi-granularity knowledge organization of standard documents, and the ontology is validated and its value elaborated through the addition of knowledge instances. The multi-granularity knowledge association method for standard organization can comprehensively reveal the multi-granularity knowledge units within standard documents, forming extensive interconnected knowledge levels and associations. This approach facilitates the effective acquisition, sharing, and reuse of standard knowledge across various service scenarios. It not only advances the construction of standard resources to suit the era of digital intelligence but also enriches the mining and utilization of document content driven by multi-granularity knowledge.

Key words: Standard documents, Knowledge organization, Semantic association, Multi granularity knowledge, Ontology construction