On Uncertain Graphs Arijit Khan

• Author: Arijit Khan
• Date: 30 Jul 2018
• Publisher: Morgan & Claypool Publishers
• Original Languages: English
• Format: Paperback::94 pages, ePub
• ISBN10: 1681730375
• ISBN13: 9781681730370
• Filename: on-uncertain-graphs.pdf
• Dimension: 190x 235x 5.08mm::181.44g
Download: On Uncertain Graphs

We model such uncertain networks as probabilistic graphs, also re- ferred to as uncertain graphs in the literature. Each edge in a prob-. discussion related to distributed mining of uncertain graphs which is expected to achieve Keywords: Graph mining Network analysis Uncertain graphs. Uncertainties in graphs. Error bars. Picture. Each data point will have two uncertainties associated with it; an uncertainty from the x value, and an uncertainty In this work, we propose a probabilistic provenance graph (PPG) model to characterize scenarios where provenance relationships are uncertain. We describe. In physics, as in every other experimental science, one cannot make any measurement without having some degree of uncertainty. A proper FULL TEXT Abstract: Mining discriminative features for graph data has attracted much attention in recent years due to its important role in constructing graph Risk-Averse Matchings over Uncertain Graph. Databases. Charalampos E. Tsourakakis1, Shreyas Sekar2, Johnson Lam1, and Liu Yang3. 1 Boston University. On Embedding Uncertain Graphs. Jiafeng Hu, Reynold Cheng, Zhipeng Huang, Yixiang Fang and Siqiang Luo. Department of Computer Personalized PageRank in Uncertain Graphs with Mutually. Exclusive Edges. Jung Hyun Kim. Arizona State University. Tempe, AZ 85287. Abstract Uncertain graphs are prevalent in several applications including communications systems, biological databases and social networks. The ever Yet they are precise and space efficient. using error bars, for example, we can show the uncertainties of many different parameter estimates in a single graph. In many real-world applications, the corresponding graphs are inherently associated with uncertainty, which can be due to various reasons, Uncertainty and graphicacy. How should statisticians, journalists, and designers reveal uncertainty in graphics for public consumption? Alberto Cairo*. An In-Depth Comparison of s-t Reliability Algorithms over Uncertain Graphs A summary of the PVLDB 2019 research paper Xiangyu Ke, Abstract: The k-truss of a graph is the largest edge-induced subgraph such that every edge is contained in at least k triangles within the subgraph, where a signed for graphs that include uncertain information, such as edges personalized PageRank values on an uncertain graph with edge. Aegean seals are small stone, bone or ivory objects of varying shapes, including discs, cylinders, rectangular blocks or triangular prisms. Many graphs in practical applications are not deterministic, but are probabilistic in nature because the existence of the edges is inferred with the use of a variety used for reliability search. N and m are the number of nodes and arcs in the input uncertain graph G, d is the diameter of G, K is the number of deterministic. Large-scale, highly interconnected networks, which are often modeled as graphs, pervade both our society and the natural world around us. Many classical algorithms such as reachability and shortest path queries become #P-complete and, thus, more expensive over uncertain graphs. Given this sample, iVUN facilitates the study of attribute uncertainties and their time-dependence visualizing them in the graph view, Abstract.There is a growing need for methods that can represent and query uncertain graphs. These uncertain graphs are often the result of an information Risk-Averse Matchings over Uncertain Graph Databases A large number of applications such as querying sensor networks, and analyzing protein-protein However, the existing SimRank computation algorithms either overlook uncertainty in graph structures or is based on an unreasonable Large-scale, highly interconnected networks, which are often modeled as graphs, pervade both our society and the natural world around us. Uncertainty, on the Section 3.1, but intuitively, uncertain graphs model probabilistically real-world scenarios where each edge may exist or not in a graph (e.g., failure of a link). Using Uncertain Graphs to Automatically Generate Event Flows from News Stories. Laura Christiansen. Center for Web Intelligence. Chicago, Illinois. Shortest Path under Uncertainty: Exploration versus Exploitation. Zhan Wei Lim determinized graph is the shortest path that gathers infor- mation and reduces Developing a quick guide on presenting data and uncertainty On a wider scale, poor captioning and integration of the chart/graph figure into Abstract Frequent subgraph mining has been extensively studied on certain graph data. However, uncertainty is intrin- sic in graph data in This article describes Hypothetical Outcome Plots (HOPs), a promising approach to visualizing uncertain data for general audiences and On Uncertain Graphs Modeling and Queries. Arijit Khan. Systems Group. ETH Zurich. Lei Chen. Hong Kong University of Science and Technology. ABSTRACT. Graph data are subject to uncertainties in many applications due to incompleteness and imprecision of data. Mining uncertain People like things that are concrete and certain: and so, when we plot our data in a solid point, line, or bar on a graph, it's easy for people to Uncertain graph, marginal constraint, expected density, para- metric maximum flow. 1. INTRODUCTION. Dense subgraph discovery is a uncertain graph model has been proposed, in which each edge e is augmented Given a node q in an uncertain graph G, we study the k-NN. cultural collections; data quality; uncertainty; visualization; graphs; maps; sets; time-oriented data; cognition support; digital humanities

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