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Traffic networks
[chapter]
2004
Handbook of Graphs and Networks
Preserved Fulltext
Early approaches to the problem have similarities to the computation of equilibrium current flow in electrical networks, with the main difference that in traffic the particles have fixed destinations. ...
Such models resemble typical molecular dynamics simulations, except that the spatial substrate is a graph instead of flat space, and particles are "intelligent". ...
Acknowledgments Los Alamos National Laboratory makes the TRANSIMS software available to academic institutions for a small charge. ...
doi:10.1002/3527602755.ch11
fatcat:5clkhcoiu5gzfkrcoidzdg6e54
Constrained shortest path query in a large time-dependent graph
2019
Proceedings of the VLDB Endowment
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We also develop parallel algorithms for the queries that guarantee to scale with big time-dependent graphs. ...
Such networks are dynamic and evolve over time, being modeled as time-dependent graphs. Therefore, in this paper, we study the CSP query over a large time-dependent graph. ...
For a timedependent graph Gt = (Vt, Et, fe(t)), we also define the static graphs Gu(Vu, Eu, Fu) as Vu = Vt, Eu = Et and Fu(e) = U (e), and G l (V l , E l , F l ) as V l = Vt, E l = Et and F l (e) = L(e ...
doi:10.14778/3339490.3339491
fatcat:453fh7y57vaxbpcl63vhma5teu
Using Local Knowledge Graph Construction to Scale Seq2Seq Models to Multi-Document Inputs
[article]
2019
arXiv
pre-print
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We show that by linearizing the graph into a structured input sequence, models can encode the graph representations within a standard Sequence-to-Sequence setting. ...
Current approaches extractively select portions of web text as input to Sequence-to-Sequence models using methods such as TF-IDF ranking. ...
These models are designed to encode sequences rather than graphs. We describe now how to convert a graph into a structured input sequence. ...
arXiv:1910.08435v1
fatcat:2epldhegyfbsxmqtb5jngtfgra
Data mining of social networks represented as graphs
2013
Computer Science Review
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Acknowledgement This research is partially supported by the Spanish MEC (project HIPERGRAPH TIN2009-14560-C03-01).
R E F E R E N C E S ...
How to represent a graph in computer memory is a key issue, due to the potentially high computational cost of many of the higher level operators we wish to perform. ...
The computation cost of generating the graph is also an issue. ...
doi:10.1016/j.cosrev.2012.12.001
fatcat:gcf6hydflzhajpo65miv2edcla
Evolutionary games on graphs
2007
Physics reports
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This review gives a tutorial-type overview of the field for physicists. ...
The major theme of the review is in what sense and how the graph structure of interactions can modify and enrich the picture of long term behavioral patterns emerging in evolutionary games. ...
This work was supported by the Hungarian National Research Fund (OTKA T-47003). ...
doi:10.1016/j.physrep.2007.04.004
fatcat:tmqmeoki55b6pi2kckdjappmfe
Dynamic Graph Learning Based on Hierarchical Memory for Origin-Destination Demand Prediction
[article]
2022
arXiv
pre-print
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To address this problem, this paper provides a dynamic graph representation learning framework for OD demands prediction. ...
However, the prediction of origin-destination (OD) demands is still a challenging problem since the number of OD pairs is usually quadratic to the number of stations. ...
Acknowledgements This work was supported by the National Natural Science Foundation of China (71901011 and U1811463) ...
arXiv:2205.14593v1
fatcat:o6ycma4sfrbcnesqz6k7j5tsoy
Graph Theory with Applications
1977
Operational Research Quarterly (1970-1977)
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Appendix I11 includes a selection of interesting graphs with special properties. These may prove to be useful in testing new conjectures. ...
Appendix I1 consists of a table in which basic properties of four graphs are listed. ...
When dealing with problems of traffic flow, for example, it is necessary to know which roads in the network are one-way, and in which direction traffic is permitted. ...
doi:10.2307/3008805
fatcat:plgnmnhvpbdzze5sxwmgubxgae
Zero-Shot Action Recognition with Three-Stream Graph Convolutional Networks
2021
Sensors
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In this paper, in order to solve these problems, we propose a three-stream graph convolutional network that processes both types of data. Our model has two parts. ...
Large datasets are often used to improve the accuracy of action recognition. However, very large datasets are problematic as, for example, the annotation of large datasets is labor-intensive. ...
For example, the presence of food in a video could indicate the action of eating or cooking. Furthermore, if a pot does not appear in the video, then this action is likely to be that of eating. ...
doi:10.3390/s21113793
pmid:34070872
fatcat:bcwm3f6bzzcndjzabjfelqsmh4
Visual Relationship Detection using Scene Graphs: A Survey
[article]
2020
arXiv
pre-print
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In this paper, we present a detailed survey on the various techniques for scene graph generation, their efficacy to represent visual relationships and how it has been used to solve various downstream tasks ...
Being one of the first papers to give a detailed survey on this topic, we also hope to give a succinct introduction to scene graphs, and guide practitioners while developing approaches for their applications ...
We would also like to thank the Institute Computer Center (ICC) IIT Roorkee for providing us with computational resources. ...
arXiv:2005.08045v1
fatcat:fzirjx3xi5dshg2bz6zkcgmg2e
Using Local Knowledge Graph Construction to Scale Seq2Seq Models to Multi-Document Inputs
2019
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
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We show that by linearizing the graph into a structured input sequence, models can encode the graph representations within a standard Sequence-to-Sequence setting. ...
Current approaches extractively select portions of web text as input to Sequence-to-Sequence models using methods such as TF-IDF ranking. ...
These models are designed to encode sequences rather than graphs. We describe now how to convert a graph into a structured input sequence. ...
doi:10.18653/v1/d19-1428
dblp:conf/emnlp/FanGBB19
fatcat:u4uju6ob7rcnvd3mqcavkgc6ey
IoTSim-Stream: Modeling stream graph application in cloud simulation
2019
Future generations computer systems
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is required to simulate the behaviour of this graph applicatir m ;" ,...,�. · computing environment. ...
In the era of big data, the high velocity of data imposes the demand for proces�. · � "uch lata in real-time to gain real-time insights. Various real-time big data platfonns/services (i.e. ...
After the selection of suitable VMs, the objects for SVM and ServiceCloudlet are created. 3. retrieve the generated scheduling plan or table. ...
doi:10.1016/j.future.2019.04.004
fatcat:dhqeykc6szh53o4v7suxnsshwi
Online Multi-Agent Forecasting with Interpretable Collaborative Graph Neural Network
[article]
2021
arXiv
pre-print
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To progressively refine predictions, multiple CoPUs are stacked to form a collaborative graph neural network. ...
We propose a novel collaborative prediction unit (CoPU), which aggregates the predictions from multiple collaborative predictors according to a collaborative graph. ...
For example, in traffic analysis, [14] builds a road network according to the urban traffic map. ...
arXiv:2107.00894v1
fatcat:4djnqe722vfx5d3xzn6oyig2by
Decision-making under risk: A graph-based network analysis using functional MRI
2012
NeuroImage
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This study also has more general paradigmatic implications for neuroeconomics, demonstrating the value of explicit modeling of inter-regional interactions for understanding the neural substrates of decisional ...
However, limited attention is given to how brain networks encode economic parameters in patterns of inter-regional interactions. ...
Acknowledgments LM was wholly funded and employed by the Fondazione IRCCS Istituto Neurologico Carlo Besta (FINCB) during the core period of ...
doi:10.1016/j.neuroimage.2012.02.048
pmid:22387471
fatcat:u4rtcjqmand4zkfq5i5t2v3dpm
A Progressive Approach for Neighboring Geosocial Communities Search Over Large Spatial Graphs
2022
IEEE Access
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Searching for neighbors for a query node in a spatial network is a fundamental problem and has been extensively investigated. ...
Analyses show that the complexity of the algorithm is decreased by an order of magnitude. Extensive experiments on real social networks confirm the superiority and effectiveness of our solutions. ...
Similar to general social networks, there is also a great need to interrogate the global organization The associate editor coordinating the review of this manuscript and approving it for publication was ...
doi:10.1109/access.2022.3168361
fatcat:anubnk5fg5f27edq4mdj7fhgmu
Self-Driving Tour Travel Route Planning Model Construction Using Recurrent Neural Network
2022
Wireless Communications and Mobile Computing
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This strategy is becoming increasingly popular among the general public, and it focuses on how to spend the least amount of money in order to visit more tourist attractions, construct the most reasonable ...
The purpose of this study is to examine the topic of self-driving travel route planning and to suggest the creation of a route planning model. ...
To improve the scientificity of the plan, the road route planning graph is regarded as a graph in graph theory, the city is regarded as a node, and the distance between the nodes is regarded as a coefficient ...
doi:10.1155/2022/5162828
fatcat:sqibijlc2rfmzjecqxciovcjdq
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