scholarly journals Label Importance Ranking with Entropy Variation Complex Networks for Structured Video Captioning

2021 ◽  
Vol 38 (4) ◽  
pp. 937-946
Author(s):  
Wenjia Tian ◽  
Yanzhu Hu
Keyword(s):  
Complex Networks ◽  
Video Captioning ◽  
Entropy Variation ◽  
Importance Ranking ◽  
Structured Video

scholarly journals Node Importance Ranking in Complex Networks Based on Multicriteria Decision Making

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Yuanzhi Yang ◽  
Lei Yu ◽  
Zhongliang Zhou ◽  
You Chen ◽  
Tian Kou
Keyword(s):  
Decision Making ◽  
Complex Networks ◽  
Multicriteria Decision Making ◽  
Practical Significance ◽  
Network Stability ◽  
Weighting Method ◽  
Multicriteria Decision ◽  
Node Importance ◽  
Subjective Factor ◽  
Importance Ranking

Measuring node importance in complex networks has great theoretical and practical significance for network stability and robustness. A variety of network centrality criteria have been presented to address this problem, but each of them focuses only on certain aspects and results in loss of information. Therefore, this paper proposes a relatively comprehensive and effective method to evaluate node importance in complex networks using a multicriteria decision-making method. This method not only takes into account degree centrality, closeness centrality, and betweenness centrality, but also uses an entropy weighting method to calculate the weight of each criterion, which can overcome the influence of the subjective factor. To illustrate the effectiveness and feasibility of the proposed method, four experiments were conducted to rank node importance on four real networks. The experimental results showed that the proposed method can rank node importance more comprehensively and accurately than a single centrality criterion.

scholarly journals Node importance ranking of complex networks

2013 ◽  
Vol 62 (17) ◽  
pp. 178901
Author(s):  
Liu Jian-Guo ◽  
Ren Zhuo-Ming ◽  
Guo Qiang ◽  
Wang Bing-Hong
Keyword(s):  
Complex Networks ◽  
Node Importance ◽  
Importance Ranking

scholarly journals Complex Network Filtering and Compression Algorithm Based on Triangle-Subgraph

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Shuxia Ren ◽  
Tao Wu ◽  
Shubo Zhang
Keyword(s):  
Complex Networks ◽  
Complex Network ◽  
Sir Model ◽  
Compression Algorithm ◽  
Sorting Algorithm ◽  
Ranking Algorithm ◽  
Original Network ◽  
Node Importance ◽  
Importance Ranking ◽  
Result Analysis

Compressing the data of a complex network is important for visualization. Based on the triangle-subgraph structure in complex networks, complex network filtering compression algorithm based on the triangle-subgraph is proposed. The algorithm starts from the edge, lists nodes of the edge and their common node sets to form a triangle-subgraph set, parses the triangle-subgraph set, and constructs new complex network to complete compression. Before calculating the set of triangle-subgraph, node importance ranking algorithm is proposed to extract high- and low-importance nodes and filter them to reduce computational scale of complex networks. Experimental results show that filtering compression algorithm can not only improve the compression rate but also retain information of the original network at the same time; sorting result analysis and SIR model analysis show that the sorting result of node importance sorting algorithm has accuracy and rationality.

Complex Networks

2009 ◽  
Author(s):  
Reuven Cohen ◽  
Shlomo Havlin
Keyword(s):  
Complex Networks

Complex Networks from Simple Rules

2013 ◽  
Vol 22 (2) ◽  
pp. 151-174 ◽  
Author(s):  
Richard Southwell ◽  
Jianwei Huang ◽  
Chris Cannings ◽  
◽  
Keyword(s):  
Complex Networks ◽  
Simple Rules
Sign in / Sign up

Export Citation Format

Share Document