This study adopts a digital humanities
approach, leveraging digital technologies to conduct multidimensional knowledge
discovery on ancient poets. It explores the resources of ancient poets across the
dimensions of “human” and “text”, “time” and “space”, “far” and “near”, aiming to form a synergy with
traditional research on ancient poets and enhance the depth and breadth of
literary and cultural history research. The study begins by constructing a
knowledge ontology model for ancient poets, providing astructured framework for
subsequent data organization. The extracted knowledge is then stored in the graph
database Neo4j, GIS database ArcGIS Pro, and Gephi software. Finally, knowledge
discovery is realized across three key areas: knowledge retrieval, knowledge
association, and knowledge inference.In particular, knowledge discovery, based
on spatiotemporal trajectories, includes spatiotemporal distribution,
spatiotemporal trajectories, and spatiotemporal discovery; whereas knowledge
discovery, based on social networks, includes overall network, individual
network, and relationship discovery.Through case studies of four famous poets
in the Tang Dynasty, this study presents the lives, works, and social
backgrounds of ancient poets from multiple dimensions, providing new research
perspectives for traditional humanities scholars.