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Compression of weighted graphs

Hannu Toivonen, Fang Zhou, Aleksi Hartikainen, Atte Hinkka
2011 Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '11  
We then propose a much wider class of tasks under the name of 'generalized weighted graph compression problem'.  ...  The interpretation (i.e. decompression) of a compressed, weighted graph is that a pair of original nodes is connected by an edge if their supernodes are connected by one, and that the weight of an edge  ...  As a final, rough illustration of weighted graph compression on real graphs, Figure 5 shows weighted graph compression on a co-authorship graph.  ... 
doi:10.1145/2020408.2020566 dblp:conf/kdd/ToivonenZHH11 fatcat:qstzqslltfhm3ntcr2v4me7u64

Scalable Compression of a Weighted Graph [article]

Kifayat Ullah Khan, Waqas Nawaz, Young-Koo Lee
2016 arXiv   pre-print
Therefore, this paper presents a scalable compression solution to compute summary of a weighted graph.  ...  All the aforementioned interactions from various domains are represented as edge weights in a graph.  ...  In this paper, we extend our set-based merging from [1] for compression of a weighted graph.  ... 
arXiv:1611.03159v1 fatcat:jjlke7hzifcale7en7mrvuw5jm

Lossy Compression of Dynamic, Weighted Graphs

Wilko Henecka, Matthew Roughan
2015 2015 3rd International Conference on Future Internet of Things and Cloud  
In this paper we present a method aimed at lossy compression of large, dynamic, weighted graphs.  ...  Large graph datasets are becoming more common as networks such as the Internet grow, and our ability to measure these graphs improves. This necessitates methods to compress these datasets.  ...  Few works consider compression of weighted graphs. In addition, many graphs evolve over time, but graph compression algorithms typically target a single static graph.  ... 
doi:10.1109/ficloud.2015.64 dblp:conf/ficloud/HeneckaR15 fatcat:udwvzbgiundkreiywd4p4wl56i

Motion-Adaptive Transforms Based on the Laplacian of Vertex-Weighted Graphs

Du Liu, Markus Flierl
2014 2014 Data Compression Conference  
The vertex weights determine only the first basis vector of the linear transform uniquely. Therefore, we use these weights to define two Laplacians of vertex-weighted graphs.  ...  We construct motion-adaptive transforms for image sequences by using the eigenvectors of Laplacian matrices defined on vertex-weighted graphs, where the weights of the vertices are defined by scale factors  ...  vertex-weighted graphs, where the weights of the vertices are defined by scale factors.  ... 
doi:10.1109/dcc.2014.67 dblp:conf/dcc/LiuF14 fatcat:a74sawbcyzd47hynnoz3xcyohi

Image Set Compression Based on Undirected Weighted Graph

Ruituo Wang, Yao Zhao, Chunyu Lin, Huihui Bai, Meiqin Liu
2015 Journal of Information Hiding and Multimedia Signal Processing  
This paper proposes an image set compression scheme based on the undirected weighted graph.  ...  We first down sample the Y-component of all images in the image set and use correlation coefficient as the parameter of edge weight function to construct an undirected weighted graph.  ...  Science and Network Technology of Beijing(XDXX1303), SRFDP(20130009120038).  ... 
dblp:journals/jihmsp/Wang0LBL15 fatcat:eshkyyz6pfapxkrtw65uxt4e5i

Weighted Graph Compression for Parameter-free Clustering With PaCCo [chapter]

Nikola S. Mueller, Katrin Haegler, Junming Shao, Claudia Plant, Christian Böhm
2011 Proceedings of the 2011 SIAM International Conference on Data Mining  
MDL relates the clustering problem to the problem of data compression: A good cluster structure on graphs enables strong graph compression.  ...  Many popular clustering techniques are designed for vector or unweighted graph data, and can thus not be directly applied for weighted graphs.  ...  PaCCo was designed to compress the graph weights with a Gaussian distribution.  ... 
doi:10.1137/1.9781611972818.80 dblp:conf/sdm/MuellerHSPB11 fatcat:foye6vqo3zcqtelbpmrk5wmzbu

On compressing weighted time-evolving graphs

Wei Liu, Andrey Kan, Jeffrey Chan, James Bailey, Christopher Leckie, Jian Pei, Ramamohanarao Kotagiri
2012 Proceedings of the 21st ACM international conference on Information and knowledge management - CIKM '12  
To the best of our knowledge, this is the first work that compresses weighted dynamic graphs with bounded lossy compression error at any time snapshot of the graph.  ...  The bounded compression error benefits compressed graphs in that they retain good approximations of the original edge weights, and hence properties of the original graph (such as shortest paths) are well  ...  The irregular changes of weights make the compression of dynamic graphs more challenging than that of static graphs due to the additional dimension of time.  ... 
doi:10.1145/2396761.2398630 dblp:conf/cikm/LiuKCBLPR12 fatcat:73g5v23b3ba27f3h5in3f4dngq

Network Compression by Node and Edge Mergers [chapter]

Hannu Toivonen, Fang Zhou, Aleksi Hartikainen, Atte Hinkka
2012 Lecture Notes in Computer Science  
We also discuss a much wider class of tasks under the name of 'generalized weighted graph compression problem'.  ...  We give methods to compress weighted graphs (i.e., networks or BisoNets) into smaller ones.  ...  This work has been supported by the Algorithmic Data Analysis (Algodan) Centre of Excellence of the Academy of Finland (Grant 118653) and by the European Commission under the 7th Framework Programme FP7  ... 
doi:10.1007/978-3-642-31830-6_14 fatcat:3gb7fyjmzrevrkx5tupp2rr6sm

The Use of Weighted Graphs for Large-Scale Genome Analysis

Fang Zhou, Hannu Toivonen, Ross D. King, Baldo Oliva
2014 PLoS ONE  
Here we propose the use of weighted graphs as a data structure to enable large-scale phylogenetic analysis of networks.  ...  summarize sequence conservation); and we applied these types of weighted graph to survey prokaryotic metabolism.  ...  The goal of weighted graph compression is to produce a compressed graph S of a given weighted graph G at a specified compression ratio cr, such that the distance between the original and compressed graph  ... 
doi:10.1371/journal.pone.0089618 pmid:24619061 pmcid:PMC3949676 fatcat:bpnss3krkfa2dkmlauxt6xloom

Predictive graph construction for image compression

Giulia Fracastoro, Enrico Magli
2015 2015 IEEE International Conference on Image Processing (ICIP)  
In this work, we propose a new method of graph construction for graph-based image compression.  ...  In particular, because of the overhead incurred by graph transmission to the receiver, we focus our attention to develop an efficient method to construct and to code the graph representation of the image  ...  Graph compression We have compared the performance of the graph transform using a graph with unquantized weights, with quantized weights and with the predicted weights.  ... 
doi:10.1109/icip.2015.7351192 dblp:conf/icip/FracastoroM15 fatcat:ehaemv2djnekvehoggp34mypym

A Path-Compression Approach for Improving Shortest-Path Algorithms

Nabil Arman, Faisal Khamayseh
2015 International Journal of Electrical and Computer Engineering (IJECE)  
Given a weighted directed graph G=(V;E;w), where w is non-negative weight function, G' is a graph obtained from G by an application of path compression.  ...  Path compression reduces the graph G to a critical set of vertices and edges that affect the generation of shortest trees.  ...  ACKNOWLEDGEMENTS This research is funded by The Scientific Research Council, Ministry of Education and Higher Education, State of Palestine under a project number of 01/12/2013, and Palestine Polytechnic  ... 
doi:10.11591/ijece.v5i4.pp772-781 fatcat:f7n3y3n5ajfstgizt55jm2otve

Representing Graph Metrics with Fewest Edges [chapter]

T. Feder, A. Meyerson, R. Motwani, L. O'Callaghan, R. Panigrahy
2003 Lecture Notes in Computer Science  
The compression factor achieved is the ratio k between the number of edges in the original graph and the number of edges in the compressed graph.  ...  We obtain approximation algorithms for unit weight graphs that replace cliques with stars in cases where the cliques so compressed are disjoint, or when only a constant number of the cliques compressed  ...  Generic Compression Algorithm A weighted graph is a graph G with a positive weight on each edge.  ... 
doi:10.1007/3-540-36494-3_32 fatcat:uz7d6wsmzvfgncqp5kwdkj26zy

Approximate maximum weight branchings

Amitabha Bagchi, Ankur Bhargava, Torsten Suel
2006 Information Processing Letters  
We consider a special subgraph of a weighted directed graph: one comprising only the k heaviest edges incoming to each vertex.  ...  We show that the maximum weight branching in this subgraph closely approximates the maximum weight branching in the original graph. Specifically, it is within a factor of k k+1 .  ...  This scenario [12] , as well as related problems in the compression of web graphs [1] and multispectral images [16] , can be modeled as a maximum weight branching problem on a directed graph.  ... 
doi:10.1016/j.ipl.2006.02.011 fatcat:pxzthk6yn5f7jm34qafjil43j4

Routing Optimization Algorithms Based on Node Compression in Big Data Environment

Lifeng Yang, Liangming Chen, Ningwei Wang, Zhifang Liao
2017 Scientific Programming  
algorithms based on node compression involving large data, in order to realize the path selection from the starting point through a given set of nodes to reach the end within a limited time.  ...  In regard to traditional backtracking and different node compression methods, we first propose an improved backtracking algorithm for one condition in big data environment and three types of optimization  ...  Conflicts of Interest The authors declare that there are no conflicts of interest regarding the publication of this paper.  ... 
doi:10.1155/2017/2056501 fatcat:hdiwl7zpfzc47jwptor67425vm

A Fast Multi-level Layout for Social Network Visualization

Xiaolin Du, Yunming Ye, Yueping Li, Ge Song
2014 International Journal of Multimedia and Ubiquitous Engineering  
Firstly, we proposed a new graph multi-layered compression method based on random walk.  ...  We first proposed a new graph multi-layered compression method based on random walk.  ...  Our compress strategy is that we compute the weights of all vertices by Random Walk algorithm, and then compress the vertices with less weight and their uncompressed moons in the graph.  ... 
doi:10.14257/ijmue.2014.9.12.16 fatcat:zc6qhaku7zg3jksxwalh7qddmq
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