A Robust Graph Partition Method from the Path-Weighted Adjacency Matrix

2005 ◽  
pp. 362-372
Author(s):  
Huaijun Qiu ◽  
Edwin R. Hancock
Keyword(s):  
Adjacency Matrix ◽  
Graph Partition ◽  
Partition Method ◽  
Weighted Adjacency Matrix

An Interactive Graph Partition Method Through Combination of Multi-scale Analysis and Level Set

2013 ◽  
Vol 34 (9) ◽  
pp. 2078-2084 ◽  
Author(s):  
Yun-fei Wang ◽  
Du-yan Bi ◽  
De-qin Shi ◽  
Tian-jun Huang ◽  
Di Liu
Keyword(s):  
Level Set ◽  
Graph Partition ◽  
Scale Analysis ◽  
Multi Scale ◽  
Partition Method ◽  
Multi Scale Analysis

scholarly journals A new multi-level algorithm for balanced partition problem on large scale directed graphs

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Xianyue Li ◽  
Yufei Pang ◽  
Chenxia Zhao ◽  
Yang Liu ◽  
Qingzhen Dong
Keyword(s):  
Large Scale ◽  
Directed Graphs ◽  
Vlsi Design ◽  
Graph Partition ◽  
Partition Problem ◽  
Multi Level ◽  
The Stability ◽  
Recursive Partition ◽  
Balanced Partition ◽  
Partition Method

AbstractGraph partition is a classical combinatorial optimization and graph theory problem, and it has a lot of applications, such as scientific computing, VLSI design and clustering etc. In this paper, we study the partition problem on large scale directed graphs under a new objective function, a new instance of graph partition problem. We firstly propose the modeling of this problem, then design an algorithm based on multi-level strategy and recursive partition method, and finally do a lot of simulation experiments. The experimental results verify the stability of our algorithm and show that our algorithm has the same good performance as METIS. In addition, our algorithm is better than METIS on unbalanced ratio.

An Algorithm for Determining the Position and Orientation of 3-D Objects from Images Using Spectral Graph Theory

2015 ◽  
Vol 770 ◽  
pp. 585-591
Author(s):  
Alexey Barinov ◽  
Aleksey Zakharov
Keyword(s):  
Graph Theory ◽  
Adjacency Matrix ◽  
Spectral Decomposition ◽  
Spectral Graph Theory ◽  
Feature Points ◽  
Image Comparison ◽  
Spectral Graph ◽  
Position And Orientation ◽  
Weighted Adjacency Matrix

This paper describes an algorithm for computing the position and orientation of 3-D objects by comparing graphs. The graphs are based on feature points of the image. Comparison is performed by a spectral decomposition with obtaining eigenvectors of weighted adjacency matrix of the graph.

scholarly journals Social Network of Faculties According to Student Preferences in Transition to Higher Education

2012 ◽  
Vol 51 (1) ◽  
pp. 51-56
Author(s):  
Güneş Mutlu ◽  
Ahmet Mete Çilingirtürk
Keyword(s):  
Social Network ◽  
Adjacency Matrix ◽  
Euclidean Distance ◽  
Student Preferences ◽  
Transition To Higher Education ◽  
Faculty Preference ◽  
The Relationship ◽  
Day By Day ◽  
Weighted Adjacency Matrix ◽  
Squared Euclidean Distance

In social network analysis, the studies on weighted adjacency matrix of nodes are increasing day by day. In thispaper, a method is proposed by including node properties to neighbourhood matrix, in order to see the structures of weightedadjacency matrix that defines the relationship between the nodes. In accordance with this proposal, the relationship betweenthe faculties of Turkish universities is studied according to student preferences. Weighted adjacency matrix between facultiesis composed based on the frequency of faculty preference of students. By using the properties of faculties, this matrix ismultiplied by the adjacency matrix, calculated by Squared Euclidian Distance. The weighted adjacency matrix of the facultiesis compared with the re-calculated weighted adjacency matrix. It is observed that the relations between faculties are turnedout to be more meaningful in new weighted neighbourhood matrix which is multiplied by Squared Euclidean Distance.

Content-Based Keyframe Clustering Using Near Duplicate Keyframe Identification

2013 ◽  
pp. 1-19
Author(s):  
Ehsan Younessian ◽  
Deepu Rajan
Keyword(s):  
Adjacency Matrix ◽  
Visual Similarity ◽  
Object Motion ◽  
Second Step ◽  
Identification Algorithm ◽  
Clustering Method ◽  
Keypoint Matching ◽  
Method Performance ◽  
News Video ◽  
Weighted Adjacency Matrix

In this paper, the authors propose an effective content-based clustering method for keyframes of news video stories using the Near Duplicate Keyframe (NDK) identification concept. Initially, the authors investigate the near-duplicate relationship, as a content-based visual similarity across keyframes, through the Near-Duplicate Keyframe (NDK) identification algorithm presented. The authors assign a near-duplicate score to each pair of keyframes within the story. Using an efficient keypoint matching technique followed by matching pattern analysis, this NDK identification algorithm can handle extreme zooming and significant object motion. In the second step, the weighted adjacency matrix is determined for each story based on assigned near duplicate score. The authors then use the spectral clustering scheme to remove outlier keyframes and partition remainders. Two sets of experiments are carried out to evaluate the NDK identification method and assess the proposed keyframe clustering method performance.

On the spectral radius and energy of the weighted adjacency matrix of a graph

2019 ◽  
Vol 340 ◽  
pp. 156-163
Author(s):  
Baogen Xu ◽  
Shuchao Li ◽  
Rong Yu ◽  
Qin Zhao
Keyword(s):  
Spectral Radius ◽  
Adjacency Matrix ◽  
Weighted Adjacency Matrix

scholarly journals A New Multi-level Algorithms for Balanced Partition Problem on Large Scale Directed Graphs

2021 ◽  
Author(s):  
Xianyue Li ◽  
Yufei Pang ◽  
Chenxia Zhao ◽  
Yang Liu ◽  
Qingzhen Dong
Keyword(s):  
Large Scale ◽  
Directed Graphs ◽  
Vlsi Design ◽  
Graph Partition ◽  
Partition Problem ◽  
Multi Level ◽  
The Stability ◽  
Recursive Partition ◽  
Balanced Partition ◽  
Partition Method

Abstract Graph partition is a classical combinatorial optimization and graph theory problem, and it has a lot of applications, such as scientific computing, VLSI design and clustering etc. In this paper, we study the partition problem on large scale directed graphs under a new objective function, a new case of graph partition problem. We firstly propose the modeling of this problem, then design an algorithm based on multi-level strategy and recursive partition method, and finally do a lot of simulation experiments. The experimental results verify the stability of our algorithm and show that our algorithm has the same good performance as METIS. In addition, our algorithm is better than METIS on unbalanced ratio.

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