In graph theory, one of the most important problems is graph labeling. Labeling of graph has a very wide range of applications in [Formula: see text]-ray crystallography, missile guidance, coding theory, signal processing, radar, data base management, astronomy, communication network addressing, ...
The field of Graph Theory plays vital role in various fields. One of the important areas in graph theory is Graph Labeling used in many applications like coding theory, x-ray crystallography, radar, astronomy, circuit design, communication network addressing, data base management. This paper gives...
There are many problems in graph theory, where labeling of graphs is the only alternative to solve it. Graph labeling widely appeared in frequency assignme... S Amanathulla,J Khatun,M Pal - 《International Journal of Mathematics for Industry》 被引量: 0发表: 2023年 ...
Discriminative Training Methods for Hidden Markov Models:Theory and Experiments with Perceptron Algorithms (2002)Michael Collins 结构化感知器将经典感知器概括为结构化预测问题,其中每个输入的可能"标签"的数目是非常大的集合,并且每个标签都具有丰富的内部结构。 ParaCrawl Corpus In order to recover them, rese...
摘要 One famous open problem in graph theory is the Graceful Tree Conjecture, which states that every finite tree has a graceful labeling. In 1973, Kotzig (Util Math 4:261-290, 1973) proved that if a leaf of a long enough path is identified with any vertex of an arbitrary tree, the ...
摘要: Sum labeling L of a graph G(V,E) is an injective labeling from V to a set of distinct positive integers S such that xy鈭圗 if and only if there is a vertex w in V such that L(w)=L(x)+L(y)鈭圫. In such...
The problem of radio channel assignments with multiple levels of interference depending on distance can be modelled using graph theory. The authors previously introduced a model of labeling by real numbers. Given a graph G, possibly infinite, and real numbers k 1, k 2 ≥ 0, an L(k 1, k...
Inform. Theory, IT-12 (1966), pp. 148-153 View in ScopusGoogle Scholar [2] M.A. Breuer, J. Folkman An unexpected result on coding the vertices of a graph J. Math. Anal. Appl., 20 (1967), pp. 583-600 View PDFView articleView in ScopusGoogle Scholar [3] C. Gavoille, D. ...
In this paper, we provide a theory of using graph neural networks (GNNs) for multi-node representation learning (where we are interested in learning a representation for a set of more than one node, such as link). We know that GNN is designed to learn single-node representations. When we...
Connected component labeling (alternatively connected component analysis) is an algorithmic application of graph theory, where subsets of connected components are uniquely labeled based on a given heuristic. Connected component labeling is not to be confused with segmentation. Connected component labeling is...