# Construction of a 3D Model Knowledge Base Based on Feature Description and Common Sense Fusion
## 3 Method
### Feature-to-Semantic Mapping Rules
#### 3.1.3 Three-Dimensional Model Ontology  
The design of the ontology can be either top-down based on classification, or bottom-up based on extraction from existing knowledge bases. We combine the two methods, first designing the basic ontology and then constructing the corpus in the corresponding positions from bottom to top. In addition, the basic ontology itself and the instances are unified as entities to form an integrated knowledge base to achieve reasoning and strengthen the description and interoperability functions. In the construction method of a machine-readable comprehensive knowledge base based on ontology, the ontology establishes a broad hierarchical structure, and all concepts are assigned under the three root categories of existence, science, and part of speech [27]. The 3D model knowledge base is intended to associate heterogeneous data, such as text, pictures, and 3D mesh surfaces. When updating the corresponding description equivalent to text and surface meshes in the knowledge base, the corresponding interoperability will be carried out. For example, if the size description of the model in the knowledge base is changed, the corresponding size of the 3D model will be updated. The hierarchical classification in the ontology design draws inspiration from the machine-readable comprehensive knowledge base construction method, while the relationship selection draws inspiration from ConceptOnto. All knowledge is organized in the form of triples, and the generation of entities and relationships is the core of ontology development. For the case of an entity attribute name and attribute value, the attribute name is defined as a relationship, and the attribute value is defined as an abstract description entity. In the abstract description entity, it can be a numerical value or a vector. All entities appear in the form of strings and are read according to different applications before being converted to the corresponding data type. The establishment of a top-down specification for the 3D model knowledge foundation ontology automatically aligns the semantic description obtained in Section 3.1 and the corresponding knowledge in the ConceptNet common sense database to the classification of the ontology. The knowledge representation with weighted digraph structure is realized by the sparse-matrix-integrated semantic dictionary. Based on the constructed 3D model knowledge base, the application of relational property reasoning, 3D model semantic retrieval, semantic interoperability, etc., can be realized. The hierarchical structure of the basic ontology is shown in Figure 2. Existence and science are the highest levels, and the classification in science is consistent with the machine-readable comprehensive knowledge base ontology, preparing for expanding knowledge. For example, adding specialized knowledge such as the density and material of objects that cannot be directly extracted from three-dimensional shapes. Existence is the core of the representation of the 3D model after knowledge extraction, which is divided into physical existence and abstract existence. Figure 2: The hierarchical structure of the basic ontology of the 3D model knowledge base. The hierarchical structure is beneficial for the inheritance of attributes, and the standardization of relationships is the key to improving the ability to describe knowledge. We include supersets and instances in relational terms, as well as attribute names, such as height, width, thickness, color, and angle, to adapt to the unified representation of the graph structure. In order to automatically add existing knowledge in the ConceptNet common sense database, we select the set relationships to include in the ontology's relationship words. As shown in Table 1, the first column contains the naming of the relationship, the second column contains the characteristics of the relationship, the third column displays the opposite relationship, and the fourth column contains the original relationship name selected in ConceptOnto.