A Method for Scientific Cultivation Analysis Based on Knowledge Graphs

The development of big data and artificial intelligence has improved the informatization scientific planting. A cultivation analysis method based on knowledge graphs is proposed in this paper. First, logical representation ontological are combined to realize access static information dynamic experience, as well their with graphs. Second, according characteristics plant information, extraction realized via relational computing. relationship determination first derivative a multi-level classification retrieval tree structure extract experience from experimental data. Then, multimedia technology embedded RDF framework implemented, which further realizes display decision suggestions after analysis. Finally, taking perennial flowers an example, realization application performance demonstrated.