Self-organizing Hopfield network for attributed relational graph matching

1995 ◽  
Vol 13 (1) ◽  
pp. 61-73 ◽  
Author(s):  
PN Suganthan ◽  
EK Teoh ◽  
DP Mital
Keyword(s):  
Graph Matching ◽  
Hopfield Network ◽  
Attributed Relational Graph ◽  
Self Organizing

Similarity Assessment for Assembly Model Based on Component Attributed Relational Graph Matching

2012 ◽  
Vol 215-216 ◽  
pp. 270-274 ◽  
Author(s):  
Song Qiao Tao ◽  
Wei He
Keyword(s):  
Graph Matching ◽  
Assessment Method ◽  
Academic Community ◽  
Assembly Model ◽  
Similarity Assessment ◽  
3D Cad ◽  
Attributed Relational Graph ◽  
Model Similarity ◽  
Component Models ◽  
3D Cad Model Retrieval

3D CAD model retrieval has received a lot of attentions in the academic community. Most existent methods for 3D model similarity assessment focus on component models instead of assembly models. In this paper, an assembly model similarity assessment method is presented in order to find the similar assemblies model for design reuse. First, assembly model is described as component attributed relational graph. Then, the compatibility matrix between two assemblies is calculated, which serves as the measure of their similarity. Finally, the optimal matching under the measures is calculated using Hungarian Method. Experimental results show that this method is able to support the assembly similarity evaluation.

Attributed relational graph matching based on the nested assignment structure

2010 ◽  
Vol 43 (3) ◽  
pp. 914-928 ◽  
Author(s):  
Duck Hoon Kim ◽  
Il Dong Yun ◽  
Sang Uk Lee
Keyword(s):  
Graph Matching ◽  
Attributed Relational Graph

scholarly journals Macro-Cell Placement for Custom-Chip Design Using Self-Organizing Fuzzy Technique

VLSI Design ◽  
1998 ◽  
Vol 7 (4) ◽  
pp. 385-399
Author(s):  
Ray-I Chang ◽  
Pei-Yung Hsiao
Keyword(s):  
Expert Knowledge ◽  
Optimization Technique ◽  
Parallel Architecture ◽  
Hopfield Network ◽  
Placement Problem ◽  
Chip Design ◽  
Macro Cell ◽  
Large Size ◽  
Cell Placement ◽  
Self Organizing

In this paper, a new optimization technique called SOFT(self-organizing fuzzy technique) is proposed to solve the macro-cell placement problem. In SOFT, different criteria are simultaneously accounted by a novel fuzzy gain function which models expert knowledge to control the optimization process. The presented procedure is an adaptation of Kohonen's self-organization algorithm which is well suited for implementation on massively parallel architecture for fast computing. The MCNC benchmark examples are presented to verify the performance and feasibility of SOFT. Comparisons are made with the Hopfield network, SOAP and TimberWolf MC5.6. Experiments show that the proposed method yields an average of 17% improvement in total wire length compared with previous methods. Large size problems with 225 and 1024 arbitrarily-sized macrocells are also presented.

Automatic Online Educational Game Content Creation by Identifying Similar Chinese Characters with Radical Extraction and Graph Matching Algorithms

2010 ◽  
Vol 8 (3) ◽  
pp. 31-46 ◽  
Author(s):  
Kwong-Hung Lai ◽  
Howard Leung ◽  
Zhi-Hui Hu ◽  
Jeff K.T. Tang ◽  
Yun Xu
Keyword(s):  
Graph Matching ◽  
Educational Games ◽  
Chinese Language ◽  
Spatial Relationship ◽  
Educational Game ◽  
Chinese Characters ◽  
Matching Method ◽  
Matching Algorithm ◽  
Content Creation ◽  
Attributed Relational Graph

One of the difficulties in learning Chinese characters is distinguishing similar characters. This can cause misunderstanding and miscommunication in daily life. Thus, it is important for students learning the Chinese language to be able to distinguish similar characters and understand their proper usage. In this paper, the authors propose a game style framework to train students to distinguish similar characters. A major component in this framework is the search for similar Chinese characters in the system. From the authors’ prior work, they find the similar characters by the radical information and stroke correspondence determination. This paper improves the stroke correspondence determination by using the attributed relational graph (ARG) matching algorithm that considers both the stroke and spatial relationship during matching. The experimental results show that the new proposed method is more accurate in finding similar Chinese characters. Additionally, the authors have implemented online educational games to train students to distinguish similar Chinese characters and made use of the improved matching method for creating the game content automatically.

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