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 r...

This paper surveys the data-driven dose prediction methods investigated for knowledge-based planning (KBP) in last decade. These were classified into two major categories—traditional KBP and deep-learning (DL) methods—according to their techniques of utilizing previous knowledge. Traditional include studies that require geometric or anatomical features either find best-matched case(s) from a re...

Discover the deep semantics from massively structured data in knowledge graph and provide reasonable explanations are a series of important foundational research issues artificial intelligence. However, hidden between entities cannot be well expressed. Moreover, considering many predicates express fuzzy relationships, existing reasoning methods effectively deal with these interpret correspondin...

An increasingly relevant theme for knowledge-based systems is how to model and use a large and complex knowledge domain. On the one hand, this involves developing new ideas on a modular construction of a knowledge base and, on the other hand, an appropriate architecture of a knowledge-based system that takes account of such a modular knowledge base. In the HYPERCON project we conceptualize a co...

The problem of comparing and matching different learners’ knowledge arises when assessment systems use a one-dimensional numerical value to represent “knowledge level”. Such assessment systems may measure inconsistently because they estimate this level differently and inadequately. The multi-dimensional competency model called COMpetence-Based learner knowledge for personalized Assessment (COMB...