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GRAPH EQUATIONS FOR LINE GRAPHS, TOTAL GRAPHS AND MIDDLE GRAPHS

GRAPH EQUATIONS FOR LINE GRAPHS, TOTAL GRAPHS AND MIDDLE GRAPHS
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Knowledge Graphs: Opportunities and Challenges [PDF]

Artificial Intelligence Review, 2023
With the explosive growth of artificial intelligence (AI) and big data, it has become vitally important to organize and represent the enormous volume of knowledge appropriately.
Feng Xia
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Random graphs

ACM-SIAM Symposium on Discrete Algorithms, 2006
We will review some of the major results in random graphs and some of the more challenging open problems. We will cover algorithmic and structural questions. We will touch on newer models, including those related to the WWW.
A. Frieze
semanticscholar   +1 more source

YAO GRAPHS SPAN THETA GRAPHS

Discrete Mathematics, Algorithms and Applications, 2010
Yao and Theta graphs are defined for a given point set and a fixed integer k > 0. The space around each point is divided into k cones of equal angle, and each point is connected to a nearest neighbor in each cone. The difference between Yao and Theta graphs is in the way the nearest neighbor is defined: Yao graphs minimize the Euclidean distance ...
Damian, Mirela, Raudonis, Kristin
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GRAPH PROCESSES

Fundamenta Informaticae, 1996
We first give a new definition of graph grammars, which, although following the algebraic double-pushout approach, is more general than the classical one because of the use of a graph of types where all involved graphs are mapped to. Then, we develop a process-based semantics for such (typed) graph grammars, in the line of processes as normally used ...
CORRADINI, ANDREA, MONTANARI, UGO GIOVANNI ERASMO, Rossi F.   +2 more
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Specifying Knowledge Graph with Data Graph, Information Graph, Knowledge Graph, and Wisdom Graph

International Journal of Software Innovation, 2018
Knowledge graphs have been widely adopted, in large part owing to their schema-less nature. It enables knowledge graphs to grow seamlessly and allows for new relationships and entities as needed. A knowledge graph is a graph constructed by representing each item, entity and user as nodes, and linking those nodes that interact with each other via edges.
Yucong Duan, Lixu Shao, Gongzhu Hu
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Graphs

Chest, 2006
Two rules of good graphs are presented and explicated.
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Graph–Graph Similarity Network

IEEE Transactions on Neural Networks and Learning Systems
Graph learning aims to predict the label for an entire graph. Recently, graph neural network (GNN)-based approaches become an essential strand to learning low-dimensional continuous embeddings of entire graphs for graph label prediction. While GNNs explicitly aggregate the neighborhood information and implicitly capture the topological structure for ...
Han Yue, Pengyu Hong, Hongfu Liu
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Graph Decomposition of Slim Graphs

Graphs and Combinatorics, 1999
Let \(H\) be a fixed graph. An \(H\)-decomposition of an input graph \(G\) is a partition of the edge set of \(G\) such that each part forms a subgraph isomorphic to \(H\). This problem is known to be NP-complete as soon as \(H\) has a component with at least three edges. (This was conjectured by Holyer, and proved independently by \textit{D. Dor} and \
Caro, Yair, Yuster, Raphael
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Graphs Within Graphs

1998
Abstract We met with spanning trees of a graph in the first chapter and with spanning circuits in the second. We shall next be concerned with spanning subgraphs satisfying certain valency conditions.
John Ball, Dominic Welsh
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