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OrthoNet: Multilayer Network Data Clustering
[article]
2020
arXiv
pre-print
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Specifically, we design a generic two-step algorithm for multilayer network data clustering. ...
We demonstrate with an extensive set of experiments on synthetic and real datasets that our method leads to a significant improvement w.r.t. state-of-the-art multilayer graph clustering algorithms, as ...
These methods can be useful when a unified representation for the multiple views is not easy to find in the data. ...
arXiv:1811.00821v5
fatcat:vmggeipeynfsdfaj4wolvwwz3i
Graph Models for Biological Pathway Visualization: State of the Art and Future Challenges
[article]
2021
arXiv
pre-print
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The contribution will, therefore, lie in providing guidelines and challenges of using multilayer networks as a unified data structure for the biological pathway visualization. ...
The concept of multilayer networks has become recently integrated into complex systems modeling since it encapsulates a very general concept of complex relationships. ...
In practice, we can use multilayer graphs as a unified graph structure because the graphs described in Sections 2.1-2.5 are specific subsets of multilayer graphs. ...
arXiv:2110.04808v1
fatcat:usdekhyy7zcezdxggpl35oy5wu
NO SQL Database: Graph database
2022
Egyptian Journal of Artificial Intelligence
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Also, this survey points to a type of NoSQL database called graph database. ...
It can be characterized as those in which the architecture for instances and schema are demonstrated as graphs and data control is described by graph oriented processes and activities and type constructors ...
Then, a graph database is utilized to store data model by the system as explained in Fig. 6 . ...
doi:10.21608/ejai.2022.132961.1002
fatcat:5laeuscc6namtif5nixb4tmrca
A Graph Framework for Multimodal Medical Information Processing
[article]
2017
arXiv
pre-print
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2016 pre-print arXiv:1608.00134v1 fatcat:qv44tjczrvgtnp6m3kkxice5na
This paper presents a framework for retrieving, analyzing, and storing medical information as a multilayer graph, an abstract format suitable for data fusion and further processing. ...
At the same time, this paper addresses the need for reliable medical information through co-author graph ranking. ...
For a review of the graph property model see [7] [6] . Neopython is a Python interface for Neo4j which allows the formation of dynamic Cypher queries as Python strings. ...
arXiv:1608.00134v2
fatcat:7wyun724jjbwxcfsavzuiqn2fe
Graphs, Convolutions, and Neural Networks: From Graph Filters to Graph Neural Networks
2020
IEEE Signal Processing Magazine
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etwork data can be conveniently modeled as a graph signal, where data values are assigned to nodes of a graph that describes the underlying network topology. ...
Successful learning from network data is built upon methods that effectively exploit this graph structure. ...
Since the training data comes from a distribution that has a graph structure S, we expect the learned map ( ; , ) x S H U ) to generalize and perform well for data x T " that come from a similar distribution ...
doi:10.1109/msp.2020.3016143
fatcat:qoxiwbtg25cxri6inqynyguyvi
Interactive graph matching and visual comparison of graphs and clustered graphs
2012
Proceedings of the International Working Conference on Advanced Visual Interfaces - AVI '12
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Interactive graph matching is based on a multi-layered interaction model and on a visual reification of graph matching functions. ...
clustering algorithms for comparison purposes. ...
The idea of treating a graph like a scatterplot has also been successfully used for the purpose of data exploration [16] . ...
doi:10.1145/2254556.2254654
dblp:conf/avi/HascoetD12
fatcat:prgxpxstqrczljrgzalfztqv44
Multilayer Network Analysis of Oil Linkages
2020
Econometrics Journal
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A multi-layer, multi-country network is extracted through a novel Bayesian graphical vector autoregressive model, which allows for a more comprehensive, dynamic representation of the network linkages than ...
The model outcome is a set of time-varying graphical networks which unveil both static representations of world oil linkages and variations in micro-economic relationships both within and between oil producers ...
The monthly crude supply can be found in the IEA MODS database (Monthly Oil Data Service). ...
doi:10.1093/ectj/utaa003
fatcat:4z66kzxz3nhhrih2ac3mvrofda
Arena3Dweb: Interactive 3D visualization of multilayered networks
[article]
2020
bioRxiv
pre-print
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In this study, we present Arena3Dweb, the first, fully interactive and dependency-free, web application which allows the visualization of multilayered graphs in 3D space. ...
For clearer and more informative views, users can choose between a plethora of layout algorithms and apply them on a set of selected layers either individually or in combination. ...
force-directed layout places the vertices on a 2D plane by simulating a physical model of springs.• Large Graph Layout (LGL) : A force-directed layout suitable for larger graphs. ...
doi:10.1101/2020.11.20.391318
fatcat:ey4twgwwdjedrp77se6oirx6uy
Arena3Dweb: interactive 3D visualization of multilayered networks
2021
Nucleic Acids Research
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In this study, we present Arena3Dweb, the first, fully interactive and dependency-free, web application which allows the visualization of multilayered graphs in 3D space. ...
For clearer and more informative views, users can choose between a plethora of layout algorithms and apply them on a set of selected layers either individually or in combination. ...
F.B. generated all the necessary data related to the case studies. N.A.P. benchmarked the tool. R.S. conceived new concepts which make Arena3D web more accessible than Arena3D. ...
doi:10.1093/nar/gkab278
pmid:33885790
pmcid:PMC8128064
fatcat:ggrcxyc22zdozonu4mnr7zoddu
Visual Analytics of Multilayer Networks Across Disciplines (Dagstuhl Seminar 19061)
2019
Dagstuhl Reports
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They are often flattened to a single network, even though real-world systems are more accurately modelled as a set of interacting networks, or layers, with different node and edge types. ...
A number of sub-topics were identified that require further research: A unifying visualization framework, Novel Visual Encodings, Analytic and Attributes, Interaction, Evaluation, Use Cases and Human Factors ...
This concept has been explored in the context of bipartite graphs by Latapy et al., with the notion of node redundancy [2]. Kivelä et al. [3] also refer to a range of metrics for relating layers. ...
doi:10.4230/dagrep.9.2.1
dblp:journals/dagstuhl-reports/KivelaMMRL19
fatcat:bokbhcjg3rhdjjtbb3wjyoikh4
Graph Attention Networks
[article]
2018
arXiv
pre-print
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a protein-protein interaction dataset (wherein test graphs remain unseen during training). ...
We present graph attention networks (GATs), novel neural network architectures that operate on graph-structured data, leveraging masked self-attentional layers to address the shortcomings of prior methods ...
Special thanks to: Benjamin Day and Fabian Jansen for kindly pointing out issues in a previous iteration of the paper; Michał Drożdżal for useful discussions, feedback and support; and Gaétan Marceau for ...
arXiv:1710.10903v3
fatcat:6xbvqpuxsjfuhfo7vqcdjmefgq
Multilayer traffic engineering for GMPLS-enabled networks
2005
IEEE Communications Magazine
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integrated model [4, 5] . ...
In these multilayer environments, a single GMPLS control plane drives various distinct switching layers at the same time and as a coherent whole, taking benefit from the "common" property of GMPLS. ...
For example, TE links not having enough bandwidth could be pruned from the TE database and not appear in the graph. Other TE attributes could be used to assign a cost to the links of the graph. ...
doi:10.1109/mcom.2005.1470810
fatcat:bqrl24mhuvg5rc64o7rhshyaey
Community Detection in Multi-Layer Graphs
2015
SIGMOD record
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The multiple aspects of interactions can be modeled as a multi-layer graph comprised of multiple interdependent graphs, where each graph represents an aspect of the interactions. ...
The goal of community detection is to partition vertices in a complex graph into densely-connected components socalled communities. ...
In the first part, a Bayesian probabilistic model is proposed for community detection over a clustered attributed graph. ...
doi:10.1145/2854006.2854013
fatcat:fvcjjhdsxre2voqdowbeond3te
A Deep Graph Embedding Network Model for Face Recognition
[article]
2014
arXiv
pre-print
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In this paper, we propose a new deep learning network "GENet", it combines the multi-layer network architec- ture and graph embedding framework. ...
Secondly, many cascaded dimensionality reduction layers based on graph embedding framework are applied to GENet. Finally, a linear SVM classifier is used to classify dimension-reduced features. ...
GRAPH EMBEDDING FRAMEWORK To represent each vertex of a graph as a low-dimensional vector, Yan [1] has proposed a general framework called graph embedding to offer a unified view for understanding and ...
arXiv:1409.7313v1
fatcat:ttz5uueycjg5xgltyexfv55l7q
CT-Mapper: Mapping Sparse Multimodal Cellular Trajectories using a Multilayer Transportation Network
[article]
2016
arXiv
pre-print
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Such a network is modeled by a large multilayer graph in which the nodes correspond to metro/train stations or road intersections and edges correspond to connections between them. ...
Since cell phone data can be captured in a passive way for a large user population, they can be harnessed to collect well-sampled mobility information. ...
We would also thanks Marco Fiore for his helpful discussion on this topic. ...
arXiv:1604.06577v1
fatcat:6epd2pihlzadpefo72kbbvimui
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