An application typically has many conceptually separate pieces of behavior written over a common class graph. Each behavior makes different assumptions about the form of the class graph and the methods provided by the classes. The behaviors’ overlapping assumptions make it difficult to modify the class graph in mid-development; each modification can break assumptions that must be tracked down a...

Graph similarity computation aims to predict a score between one pair of graphs facilitate downstream applications, such as finding the most similar chemical compounds query compound or Fewshot 3D Action Recognition. Recently, some graph models based on neural networks have been proposed, which are either graph-level interaction node-level comparison. However, when number nodes in increases, it...

Although multi-view clustering (MVC) has achieved remarkable performance by integrating the complementary information of views, it is inefficient when facing scalable data. Proverbially, anchor strategy can mitigate such a challenge certain extent. However, unsupervised dynamic usually cannot obtain optimal anchors for MVC. The main reasons are that does not consider fairness different views an...

let $g=(v,e)$ be a simple graph. a set $ssubseteq v$ isindependent set of $g$,  if no two vertices of $s$ are adjacent.the  independence number $alpha(g)$ is the size of a maximumindependent set in the graph. in this paper we study and characterize the independent sets ofthe zero-divisor graph $gamma(r)$ and ideal-based zero-divisor graph $gamma_i(r)$of a commutative ring $r$.

Chemoinformatics is a well established research field concerned with the discovery of molecule’s properties through informational techniques. Computer science’s research fields mainly concerned by the chemoinformatics field are machine learning and graph theory. From this point of view, graph kernels provide a nice framework combining machine learning techniques with graph theory. Such kernels ...

A power law degree distribution is established for a graph evolution model based on the graph class of k-trees. This k-tree-based graph process can be viewed as an idealized model that captures some characteristics of the preferential attachment and copying mechanisms that existing evolving graph processes fail to model due to technical obstacles. The result also serves as a further cautionary ...

This theoretical paper aims to provide a probabilistic framework for graph signal processing. By modeling signals on graphs as Gaussian Markov Random Fields, we present numerous important aspects of graph signal processing, including graph construction, graph transform, graph downsampling, graph prediction, and graph-based regularization, from a probabilistic point of view. As examples, we disc...

The rationale of product platform-based product development has been well recognized for the implementation of mass customization. A product platform refers to the conceptual structure and logical organization of product families from both customer and technical viewpoints. This paper introduces graph grammar formalisms to the representation of product platform. The concepts of multi-pointed hy...