# Research on the Detection Method of Implicit Self Symmetry in a High-Level Semantic Model

## Abstract

**:**

## 1. Introduction

## 2. Methods

#### 2.1. Semantic Analysis of Model Set

#### 2.2. Self-Symmetry Detection of High-Level Semantic Model Based on Skeleton

## 3. Results

#### 3.1. Execution Time of Different Methods

#### 3.2. Accuracy of Different Methods

#### 3.3. Symmetric Performance Test Comparison

## 4. Conclusions

- (1)
- The designed model has short execution time and high detection efficiency.
- (2)
- The designed model has significantly higher detection accuracy than other traditional methods and high detection accuracy.
- (3)
- The designed model can reduce the interference of topological noise, accurately detect local characteristics, and has higher symmetrical performance.

## Funding

## Conflicts of Interest

## References

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## Share and Cite

**MDPI and ACS Style**

Wang, C.
Research on the Detection Method of Implicit Self Symmetry in a High-Level Semantic Model. *Symmetry* **2020**, *12*, 28.
https://doi.org/10.3390/sym12010028

**AMA Style**

Wang C.
Research on the Detection Method of Implicit Self Symmetry in a High-Level Semantic Model. *Symmetry*. 2020; 12(1):28.
https://doi.org/10.3390/sym12010028

**Chicago/Turabian Style**

Wang, Chao.
2020. "Research on the Detection Method of Implicit Self Symmetry in a High-Level Semantic Model" *Symmetry* 12, no. 1: 28.
https://doi.org/10.3390/sym12010028