scholarly journals Distributed temporal graph analytics with GRADOOP

2021 ◽  
Author(s):  
Christopher Rost ◽  
Kevin Gomez ◽  
Matthias Täschner ◽  
Philip Fritzsche ◽  
Lucas Schons ◽  
...  
Keyword(s):  
Graph Model ◽  
Lessons Learned ◽  
Temporal Property ◽  
Graph Analytics ◽  
Matching Graph ◽  
Temporal Graph ◽  
Scalable Analysis ◽  
Temporal Graphs ◽  
Distributed Analytics ◽  
Difference Pattern

AbstractTemporal property graphs are graphs whose structure and properties change over time. Temporal graph datasets tend to be large due to stored historical information, asking for scalable analysis capabilities. We give a complete overview of Gradoop, a graph dataflow system for scalable, distributed analytics of temporal property graphs which has been continuously developed since 2005. Its graph model TPGM allows bitemporal modeling not only of vertices and edges but also of graph collections. A declarative analytical language called GrALa allows analysts to flexibly define analytical graph workflows by composing different operators that support temporal graph analysis. Built on a distributed dataflow system, large temporal graphs can be processed on a shared-nothing cluster. We present the system architecture of Gradoop, its data model TPGM with composable temporal graph operators, like snapshot, difference, pattern matching, graph grouping and several implementation details. We evaluate the performance and scalability of selected operators and a composed workflow for synthetic and real-world temporal graphs with up to 283 M vertices and 1.8 B edges, and a graph lifetime of about 8 years with up to 20 M new edges per year. We also reflect on lessons learned from the Gradoop effort.

Time-topology analysis

2021 ◽  
Vol 14 (13) ◽  
pp. 3322-3334
Author(s):  
Yunkai Lou ◽  
Chaokun Wang ◽  
Tiankai Gu ◽  
Hao Feng ◽  
Jun Chen ◽  
...  
Keyword(s):  
Temporal Information ◽  
Time Dimension ◽  
Topology Analysis ◽  
Topological Information ◽  
Analysis Methods ◽  
Short Period ◽  
Pruning Strategy ◽  
Temporal Graph ◽  
Types Of Information ◽  
Temporal Graphs

Many real-world networks have been evolving, and are finely modeled as temporal graphs from the viewpoint of the graph theory. A temporal graph is informative, and always contains two types of information, i.e., the temporal information and topological information, where the temporal information reflects the time when the relationships are established, and the topological information focuses on the structure of the graph. In this paper, we perform time-topology analysis on temporal graphs to extract useful information. Firstly, a new metric named T-cohesiveness is proposed to evaluate the cohesiveness of a temporal subgraph. It defines the cohesiveness of a temporal subgraph from the time and topology dimensions jointly. Specifically, given a temporal graph G s = ( Vs , ε Es ), cohesiveness in the time dimension reflects whether the connections in G s happen in a short period of time, while cohesiveness in the topology dimension indicates whether the vertices in V s are densely connected and have few connections with vertices out of G s . Then, T-cohesiveness is utilized to perform time-topology analysis on temporal graphs, and two time-topology analysis methods are proposed. In detail, T-cohesiveness evolution tracking traces the evolution of the T-cohesiveness of a subgraph, and combo searching finds out all the subgraphs that contain the query vertex and have T-cohesiveness larger than a given threshold. Moreover, a pruning strategy is proposed to improve the efficiency of combo searching. Experimental results confirm the efficiency of the proposed time-topology analysis methods and the pruning strategy.

Visualizing the Logic of a Clinical Guideline: A Case Study in Childhood Immunization

1997 ◽  
Vol 36 (03) ◽  
pp. 179-183 ◽  
Author(s):  
S. J. Frawley ◽  
S. M. Powsner ◽  
R. N. Shiftman ◽  
P. L. Miller ◽  
C. A. Brandt
Keyword(s):  
Time Course ◽  
Clinical Guideline ◽  
Graph Model ◽  
Visual Presentation ◽  
Lessons Learned ◽  
Patient Specific ◽  
Childhood Immunization ◽  
Factors Affecting ◽  
Visual Model ◽  
Knowledge Based

IMM/Graph is a visual model designed to help knowledge-base developers understand and refine the guideline logic for childhood immunization. The IMM/Graph model is domain-specific and was developed to help build a knowledge-based system that makes patient-specific immunization recommendations. A “visual vocabulary” models issues specific to the immunization domain, such as (1) the age a child is first eligible for each vaccination dose, (2) recommended, “past due” and maximum ages, (3) minimum waiting periods between doses, (4) the vaccine brand or preparation to be given, and (5) the various factors affecting the time course of vaccination. Several lessons learned in the course of developing IMM/Graph include the following: (1) The intended use of the model may influence the choice of visual presentation; (2) There is a potentially interesting interplay between the use of visual and textual information in creating the visual model; (3) Visualization may help a development team better understand a complex clinical guideline and may also help highlight areas of incompleteness.

Graph Analytics-Lessons Learned and Challenges Ahead

2011 ◽  
Vol 31 (5) ◽  
pp. 18-29 ◽  
Author(s):  
Pak Chung Wong ◽  
Chaomei Chen ◽  
Carsten Gorg ◽  
Ben Shneiderman ◽  
John Stasko ◽  
...  
Keyword(s):  
Lessons Learned ◽  
Graph Analytics

scholarly journals Two Influence Maximization Games on Graphs Made Temporal

2021 ◽  
Author(s):  
Niclas Boehmer ◽  
Vincent Froese ◽  
Julia Henkel ◽  
Yvonne Lasars ◽  
Rolf Niedermeier ◽  
...  
Keyword(s):  
Nash Equilibria ◽  
Dynamic Nature ◽  
Games On Graphs ◽  
Graph Games ◽  
Graph Classes ◽  
Temporal Graph ◽  
Influence Spreading ◽  
Temporal Graphs ◽  
Competitive Diffusion ◽  
Over Time

To address the dynamic nature of real-world networks, we generalize competitive diffusion games and Voronoi games from static to temporal graphs, where edges may appear or disappear over time. This establishes a new direction of studies in the area of graph games, motivated by applications such as influence spreading. As a first step, we investigate the existence of Nash equilibria in competitive diffusion and Voronoi games on different temporal graph classes. Even when restricting our studies to temporal paths and cycles, this turns out to be a challenging undertaking, revealing significant differences between the two games in the temporal setting. Notably, both games are equivalent on static paths and cycles. Our two main technical results are (algorithmic) proofs for the existence of Nash equilibria in temporal competitive diffusion and temporal Voronoi games when the edges are restricted not to disappear over time.

scholarly journals Application of Graph Analytics for Simulations of Electronic Money Turnover: Solutions, Evaluations, Forecasts

2019 ◽  
Vol 224 ◽  
pp. 06006
Author(s):  
Olga E. Pyrkina ◽  
Sergey A. Zadadaev
Keyword(s):  
System Analysis ◽  
Real Life ◽  
Graph Model ◽  
Economic Security ◽  
Centrality Measures ◽  
Electronic Money ◽  
Graph Models ◽  
Graph Analytics ◽  
Network Nodes ◽  
Graph Metric

The graph model for electronic money turnover developed in this paper considers the system of electronic money turnover as a technological complex network. This network includes systems of electronic money payments, communications between bank and its clients, and interbank communications. The application of the graph models is based on its essential advantages such as an opportunity to expand this system to arbitrary size and visualization of the system links. While graph plotting provides us with the opportunity of carrying out qualitative (visual) system analysis, e computations of the graph metric allows performing a more quantitative analysis. The composite metric, created on the base of graph centrality measures and giving us possibilities of estimating and ranking potential risks, is considered as a foundation for methods of stability, quality and economic security control for systems of the electronic money turnover. A validity of this classification has been investigated and supported by the so-called crash tests, which simulate the random consecutive deleting of graph nodes represented in the real life by communication network nodes, for example, banks or other members of electronic money turnover system, and also by the analysis of the overall performance of the system.

A Spatio-Temporal Graph Model for Marine Dune Dynamics Analysis and Representation

2013 ◽  
pp. n/a-n/a ◽  
Author(s):  
Rémy Thibaud ◽  
Géraldine Del Mondo ◽  
Thierry Garlan ◽  
Ariane Mascret ◽  
Christophe Carpentier
Keyword(s):  
Graph Model ◽  
Dynamics Analysis ◽  
Temporal Graph ◽  
Spatio Temporal ◽  
Dune Dynamics

scholarly journals Interference-free Walks in Time: Temporally Disjoint Paths

2021 ◽  
Author(s):  
Nina Klobas ◽  
George B. Mertzios ◽  
Hendrik Molter ◽  
Rolf Niedermeier ◽  
Philipp Zschoche
Keyword(s):  
Disjoint Paths ◽  
Constant Number ◽  
Underlying Graph ◽  
Traffic Routing ◽  
Temporal Graph ◽  
The One ◽  
Temporal Graphs ◽  
General Graphs ◽  
Temporal Path ◽  
Np Hardness

We investigate the computational complexity of finding temporally disjoint paths or walks in temporal graphs. There, the edge set changes over discrete time steps and a temporal path (resp. walk) uses edges that appear at monotonically increasing time steps. Two paths (or walks) are temporally disjoint if they never use the same vertex at the same time; otherwise, they interfere. This reflects applications in robotics, traffic routing, or finding safe pathways in dynamically changing networks. On the one extreme, we show that on general graphs the problem is computationally hard. The "walk version" is W[1]-hard when parameterized by the number of routes. However, it is polynomial-time solvable for any constant number of walks. The "path version" remains NP-hard even if we want to find only two temporally disjoint paths. On the other extreme, restricting the input temporal graph to have a path as underlying graph, quite counterintuitively, we find NP-hardness in general but also identify natural tractable cases.

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