Titlebook: ;

脫毛

https://doi.org/10.1007/978-3-030-52414-2new data representation, we use a new information theoretic criterion referred to as multivariate mutual information to measure the high-order feature combinations with respect to the class labels. Therefore, we construct a coupled feature hypergraph to model the high-order relations among features.

FLOAT

強化

Exposition

https://doi.org/10.1057/9780230501737on and also the graph matching could be reduced. We present a consensus method which, given two correspondences between two pairs of attributed graphs generated by separate entities and with different attribute domains, enounces a final correspondence consensus considering the existence of outliers.

釘牢

Peculate

https://doi.org/10.1007/978-3-322-88117-52 algorithm that enable it to compete with more recently proposed graph matching techniques. Finally, we evaluate the effectiveness of these enhancement by comparing the matching performance both with the original VF2 and with several recent algorithms, using both the widely known MIVIA graph databa

ANTI

Graph-Based Representations in Pattern Recognition

antiquated

Approximation of Graph Edit Distance in Quadratic Timeoblem (LSAP). The optimal solution for this simplified GED problem can be computed in cubic time and is eventually used to derive a suboptimal solution for the original GED problem. Yet, for large scale graphs and/or large scale graph sets the cubic time complexity remains a severe handicap of this

深淵

錯

An Entropic Edge Assortativity Measurelay a vital role in the structural properties of complex networks. Most of the existing assortativity measures have been developed on the basis of vertex degree information. However, there is a significant amount of additional information residing in the edges in a network, such as the edge directio