Distance and centrality computations are important building blocks for modern graph databases as well as for dedicated graph analytics systems. Two commonly used centrality metrics are the compute-intense closeness and betweenness centralities, which require numerous expensive shortest distance calculations. We...
3) Connected unweighted undirected graphs 无向非加权图 4) undirected weighted graph 无向赋权图 1. The solution-based DPCNN to the minimum spanning tree ofundirected weighted graph; 基于DPCNN的无向赋权图的最小生成树的求解 2. Undirected Weighted Graph Hamilton Path Question Based on DNA Algorithm;...
2) unweighted graph 非加权图 3) non-weighted code 非加权码 4) nonlinear weighting 非线性加权 1. Identification of underground nuclear explosions and natural earthquakes based on K-correlation ofnonlinear weighting; 基于非线性加权K-相关的核爆地震识别 ...
graph such that differences of the components provide information about the distances between the vertices.According to the distances,the SPWUG algorithm computed the initial partition of the coarsest graph by extending the Laplacian spectral graph theory from the unweighted undirected graph into the ...
A prime graph is one whose factorizations always include itself. Sabidussi [21] showed that every connected, unweighted graph has a unique factorization into prime graphs, and Feigenbaum et al. [9] and Winkler [25] first showed that the prime factorization of such graphs can be found in ...
This transformation has revealed multiscale self-similarity to be a ubiquitous symmetry in the binarized structure of real networks, and allows to obtain scaled down replicas. However, the GR technique is restricted to unweighted network representations. Information about the intensities of interactions ...
摘要: A graph is called a weighted graph if each edge e is assigned a non-negative number w(e), called the weight of e. In this paper, some theorems on the existence of long paths and cycles in unweighted graphs are generalized to weighted graphs and some related problems are proposed....
Thus, graph mining has been an active research area in recent years. Most of the graph min-ing research focuses on mining unweighted graphs. However, weighted graphs are actually more common. The weight on an edge may represent the likelihood of the existence of the edge or the strength of...
In this work, we present a new definition of weighted coreness for vertices in a weighted graph, by taking into account the weights of vertices, which makes the coreness in unweighted graph be a special case. We propose efficient algorithms for both weighted core decomposition and weighted ...
Temporal link prediction (TLP, a.k.a. dynamic link prediction) is an inference task on dynamic graphs that predicts future topology using historical graph snapshots. Existing TLP methods are usually designed for unweighted graphs with fixed node sets. Some of them cannot be generalized to the pre...