A regular graph G is called vertex transitive if the automorphism group of G contains a single orbit. In this paper we define and consider another class of regular graphs called neighborhood regular graphs abbreviated NR. In particular, let G be a graph and N [v] be the closed neighborhood of a vertex v of G. Denote by G(N [v]) the subgraph of G induced by N [v]. We call G NR if G(N [v]) ∼= G(N...

It is increasingly common to find real-life data represented as networks of labeled, heterogeneous entities. To query these networks, one often needs to identify the matches of a given query graph in a (typically large) network modeled as a target graph. Due to noise and the lack of fixed schema in the target graph, the query graph can substantially differ from its matches in the target graph i...

It is known that for a graph on n vertices bn2/4c + 1 edges is sufficient for the existence of many triangles. In this paper, we determine the minimum number of edges sufficient for the existence of k triangles intersecting in exactly one common vertex. 1 Notation With integers n ≥ p ≥ 1, we let Tn,p denote the Turán graph, i.e., the complete p-partite graph on n vertices where each partite set...

EEective reasoning about a physical system requires an appropriate mapping from the system characteristics to abstractions that match the impedance of the task at hand. In Qualitative Physics, three ontological abstractions are widely used: device, process, and constraint. We present a framework and a new ontological abstraction, the eld ontology, to unify many reasoning tasks involving image-l...

Graph Neural Networks (GNNs) are known to address such tasks over graph-structured data, which is widely used represent many real-world systems. The collection and analysis of graph data using GNNs raise significant privacy concerns regarding disclosing sensitive information. Existing works in privacy-preserving ensure the nodes’ features labels. However, its structure also needs be privatized....

. ABC analysis is one of the most widely used techniques in inventory management to classify items into three ordered categories called A, B and C, where category A contains the most important items and category C includes the least important ones. The ABC classification of inventory items is based on their performance expressed by weighted scores. In this paper, a new ABC classification model ...

The dramatic proliferation of sophisticated networks has resulted in a growing need for supporting effective querying and mining methods over such large-scale graph-structured data. At the core of many advanced network operations lies a common and critical graph query primitive: how to search graph structures efficiently within a large network? Unfortunately, the graph query is hard due to the ...

A. Berry Abstra t: Many problems related to knowledge dis overy an be modelized by an undire ted graph, whi h in turn has a strong stru ture asso iated with its minimal separators. On several well-known graph lasses whi h are used in appli ations, the graph extremities and the related elimination orderings are an eÆ ient algorithmi tool. Often, these extremities turn out to be related to the mi...

The capacitated miinimum spanning tree (CMST) problem is to find a minimum cost spanning tree with an additional cardinality constraint on the sizes of the subtrees incident to a given root node. The CMST problem is an NP-complete problem, and existing exact algorithms can solve only small size problems. Currently, the best available heuristic procedures for the CMST problem are tabu search alg...

Graph streams have been extensively studied, for instance, for data mining and for stream reasoning, while a fairly limited number of studies have been conducted on visualizations. Recently, edge bundling methods has been extensively investigated to reduce visual clutter in large graph visualizations, however, have focused on static graphs. This paper presents a new framework, namely StreamEB, ...