Abstract: 【Purpose/significance】Discover the linked relations among academic resources and their internal knowledge by structuring
and organizing academic resources semantically.【Method/process】This paper proposes a method to discover the linked relations of academic resources based on full-text knowledge network, and designs the model and construction process of full-text knowledge net⁃work. 520 full-text articles about Arabidopsis are downloaded from the Pubmed Central database. After parsing, knowledge extraction,these articles are described as fine-grained knowledge and constructed into full-text knowledge network. Then SPARQL query and RelFinder visualization tool are used to discover the linked relations between entities in three layers (academic resource layer, knowl⁃edge unit and knowledge object layer) of the knowledge network.【Result/conclusion】 This paper constructs a knowledge network to fine-grained organize and reveal academic resources, which is helpful to discover the potential relations between academic resources.It is of important significance for the deep utilization of academic resources.【Innovation/limitation】The innovation of this paper lies in the fine-grained representation, organization and further relation discovery of academic resources through the construction of full-text
knowledge network, and the limitation is that large-scale application practice has not been carried out.