A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Filters
Efficient Community Detection in Large-Scale Dynamic Networks Using Topological Data Analysis
[article]
2022
arXiv
pre-print
Preserved Fulltext
In this paper, we propose a method that extends the persistence-based topological data analysis (TDA) that is typically used for characterizing shapes to general networks. ...
We introduce the concept of the community tree, a tree structure established based on clique communities from the clique percolation method, to summarize the topological structures in a network from a ...
Supplemental Materials: Efficient Community Detection in Large-Scale Dynamic Networks Using Topological Data Analysis
S1 Design of Data Structure We assign each vertex v with a unique ID, denoted by ...
arXiv:2204.03191v1
fatcat:rowa63emrrftlmlv4envlaarlq
Visual analysis of large-scale network anomalies
2013
IBM Journal of Research and Development
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
In this paper, we provide a brief overview of several useful visualization techniques for the analysis of spatiotemporal anomalies in large-scale networks. ...
TEMG transforms network topologies into directed trees so that efficient search is more likely to be performed for anomalous changes in network behavior and routing topology in large dynamic networks. ...
In this paper, we present a brief overview of five potentially useful graph visualization techniques for anomaly analysis on large-scale network data. ...
doi:10.1147/jrd.2013.2249356
fatcat:foajq5zrmzhkfl4rnjh7hvdzei
2019 Index IEEE Transactions on Network Science and Engineering Vol. 6
2019
IEEE Transactions on Network Science and Engineering
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
., +, TNSE April -June 2019 158-172 Numerical analysis Threshold Models of Cascades in Large-Scale Networks. ...
-Dec. 2019 844-856 Threshold Models of Cascades in Large-Scale Networks. ...
Probability density function Identification of Missing Links Using Susceptible-Infected-Susceptible Spreading Traces. Vajdi, A., +, TNSE Oct.-Dec. 2019 ...
doi:10.1109/tnse.2020.2964975
fatcat:mb5jt4io7jfbdiso323jgi7hlm
Research on MAC Protocols in Cluster-Based Ad Hoc Networks
2021
Wireless Communications and Mobile Computing
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Mobile ad hoc networks can be widely used in many scenes, for example, military communication, emergency communication, and 5G wide area coverage as well as ultradense network scenes. ...
In view of multiservice simultaneous transmission demand for small-scale dense networking scene and large-scale extended networking scene, a MAC protocol based on scheduling of cluster head is proposed ...
Analysis for Large-Scale Extended Coverage Networking Scene. ...
doi:10.1155/2021/5513469
fatcat:ryhqe35uxbbfjgv7lha7uglcqq
Complex Networks, Communities and Clustering: A survey
[article]
2015
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Complex networks describe a widespread variety of systems in nature and society especially systems composed by a large number of highly interconnected dynamical entities. ...
Complex networks like real networks can also have community structure. There are several types of methods and algorithms for detection and identification of communities in complex networks. ...
As can be seen community detection in complex networks is an active research area and has got real life applications in the fields of large scale engineering, social media analysis, biomedical data analysis ...
arXiv:1503.06277v1
fatcat:6rllcyatpzblhocuny76fwpk2u
A Novel Emerging Topic Identification and Evolution Discovery Method on Time-Evolving and Heterogeneous Online Social Networks
2021
Complexity
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
; secondly, a novel dynamic community detection method is proposed by which the new emerging topic is detected on the modeled time-evolving and scalable KeyGraph network; thirdly, a unified directional ...
This paper proposed a novel early emerging topic detection and its evolution law identification framework based on dynamic community detection method on time-evolving and scalable heterogeneous social ...
E t+Δt , which enables its applications in the large-scale network. e flow chart of our proposed dynamic community detection method is presented in Figure 2 . ...
doi:10.1155/2021/8859225
doaj:66c1eb9e63284b80953f2fe3507f4ffc
fatcat:dv6xk3hr5zey3ohxoxmwdgx2ga
Dynamic Community Detection via Adversarial Temporal Graph Representation Learning
[article]
2022
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
In this work, an adversarial temporal graph representation learning (ATGRL) framework is proposed to detect dynamic communities from a small sample of brain network data. ...
Dynamic community detection has been prospered as a powerful tool for quantifying changes in dynamic brain network connectivity patterns by identifying strongly connected sets of nodes. ...
Introduction Neuroscience is emerging into a generation marked by a large amount of complex neural data obtained from large-scale neural systems [1] . ...
arXiv:2207.03580v1
fatcat:gp25wftdmjhhxefjgdrcqi6b5y
Design of Complex Network Distributed Computing Information Mining Method
2015
International Journal of Grid and Distributed Computing
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
The information that caused by the complex network is massive, but because of a large amount of information, so the use of traditional data analysis has been unable to meet the search and mining complex ...
This paper presents a data mining model matrix, according to this model can integrate different information, optimization of data mining, so as to improve the efficiency of complex network distributed ...
(No 61103143), basic and frontier project of Science and Technology Department of Henan province, China (No 142300410334), the funding scheme for young backbone teachers of colleges and universities in ...
doi:10.14257/ijgdc.2015.8.5.09
fatcat:oxmndlmbjze37jdxf6dpd4ynle
Problem Domains in Complex Networks
2016
IOSR Journal of Computer Engineering
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
In this paper most important research domains related to complex networks are reviewed such as Community detection, Influence Maximization, network sampling etc. ...
Complex networks are special graphs with non trivial topological properties-features that do not occur in simple networks such as lattices or random graphs. ...
So the modeling and analysis of such huge data is also one of the challenging problems. In order to study these massive graphs, we need to represent and process large scale graphs. ...
doi:10.9790/0661-1805026568
fatcat:nxcrszgskjbkfmgzel4ml5a4sq
Neural Signaling and Communication
[chapter]
2019
New Frontiers in Brain-Computer Interfaces [Working Title]
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
In this chapter we focus on how neurosignaling and communication is playing its part in medical psychology, furthermore, we have also reviewed how the interaction of network topology and dynamic models ...
The neuroscientific community is interested in the network architecture of the human brain its simulation and for prediction of emergent network states. ...
to a burst of data developed using a diverse array of measurement methods, and at scales fluctuating from a level of single cells to large brain areas. ...
doi:10.5772/intechopen.86318
fatcat:xy6tuwguavhetpkou5uaewgxji
Systems for Near Real-Time Analysis of Large-Scale Dynamic Graphs
[article]
2014
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
The sheer amount of data to be processed has prompted the creation of a myriad of systems that help us cope with massive scale graphs. ...
Graphs are widespread data structures used to model a wide variety of problems. ...
Some work has been done beyond topological measurements: information-theoretical adaptive algorithms. [66] use network entropy for detecting temporal uncertainty in communication networks. ...
arXiv:1410.1903v1
fatcat:axdwyivrlfev5phapnwng7jgoy
Mass Cooperative Transmission and QoS Supported Mechanism in Wireless Sensor Networks
2014
International Journal of Distributed Sensor Networks
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Zhu et al. proposes a dynamic Bayesian model averaging method for highaccuracy prediction analytics in large-scale IoT applications. ...
The simulation results show that the proposed topologies have small-world, scale-free feathers and a better performance in improving energy efficiency and enhancing network robustness. ...
Zhu et al. proposes a dynamic Bayesian model averaging method for highaccuracy prediction analytics in large-scale IoT applications. ...
doi:10.1155/2014/363584
fatcat:3dgywtg7ezehhl42norpkzemue
Graph theory methods: applications in brain networks
2018
Dialogues in Clinical Neuroscience
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
Network neuroscience is a thriving and rapidly expanding field. Empirical data on brain networks, from molecular to behavioral scales, are ever increasing in size and complexity. ...
A number of emerging trends are the growing use of generative models, dynamic (time-varying) and multilayer networks, as well as the application of algebraic topology. ...
A recent example used topological data analysis to reveal dynamical organization in multitask fMRI time series, by creating graphical representations of relations among single image frames at the level ...
pmid:30250388
pmcid:PMC6136126
fatcat:xgy23bv45ve3pmtu5msj73crcu
Interactive Wormhole Detection in Large Scale Wireless Networks
2006
2006 IEEE Symposium On Visual Analytics And Technology
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2011; you can also visit the original URL.
The file type is application/pdf.
This paper develops an approach, Interactive Visualization of Wormholes (IVoW), to monitor and detect such attacks in large scale wireless networks in real time. ...
We characterize the topology features of a network under wormhole attacks through the node position changes and visualize the information at dynamically adjusted scales. ...
The method introduced in this paper, Interactive Visualization of Wormhole (IVoW), provides a visual approach through which the users can detect multiple wormholes in a large scale, dynamic wireless network ...
doi:10.1109/vast.2006.261435
dblp:conf/ieeevast/WangL06
fatcat:hay3euigpbc6vn5ggjc22acm7u
RETRACTED ARTICLE: Invulnerability mechanism based on mobility prediction and opportunistic cloud computing with topological evolution for wireless multimedia sensor networks
2015
EURASIP Journal on Wireless Communications and Networking
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Experimental results show that compared with the static scheme for WMSNs, the proposed survivability mechanism has the obvious advantage in the node protection, data communication, network life cycle, ...
Finally, using the network topology reconfiguration and opportunities for cloud computing, an enhanced WMSN survivability and end-to-end quality of service guarantee mechanism was proposed. ...
consumption, and dynamic evolution of network topology in real time. ...
doi:10.1186/s13638-015-0471-6
fatcat:yawhcput7zh4nbxkmnef3xu73m
« Previous
Showing results 1 — 15 out of 64,591 results