Embedding learning is essential in various research areas, especially natural language processing (NLP). However, given the nature of unstructured data and word frequency distribution, general pre-trained embeddings, such as word2vec GloVe, are often inferior tasks for specific domains because missing or unreliable embedding. In many domain-specific tasks, pre-existing side information can be c...

Graph representation learning has become a mainstream method for processing network structured data, and most graph methods rely heavily on labeling information downstream tasks. Since labeled is rare in the real world, adopting self-supervised to solve neural problem significant challenge. Currently, existing approaches attempt maximize mutual learning, which leads large amount of redundant th...

A clique in a graph is a complete subgraph maximal under inclusion. The clique graph of a graph is the intersection graph of its cliques. A graph is self-clique when it is isomorphic to its clique graph. A circular-arc graph is the intersection graph of a family of arcs of a circle. A Helly circular-arc graph is a circular-arc graph admitting a model whose arcs satisfy the Helly property. In th...

In this paper, we consider how self-description can be realized for construction and execution in a single framework of a variant of graph rewriting systems, called graph rewriting automata. As an example of self-description for construction, a self-replication based on a self-description is shown. Meta-node structure is introduced for selfdescription for execution that enables us to embed rule...

Introduction: Today, student-centered methods must be used to train students with professional competency. One of the most valuable methods is Jigsaw (JT). Despite its various positive effects on students’ learning, not all teachers are familiar with Jigsaw. In order to familiarize teachers with this method and encourage them to use it in teaching their students, this article introduces Jigsaw,...

We present new serial and parallel algorithms for multilevel graph partitioning. Our algorithm has coarsening, partitioning and uncoarsening phases like other multilevel partitioning methods. However, we choose fixed nodes which are at least a specified distance away from each other and coarsen them with their neighbor nodes in the coarsening phase using various heuristics. Using this algorithm...

In this paper we propose a self-organizing method for the graph colouring problem. The proposed self-organizing method for the graph colouring extends the chemical casting model and makes it possible to find the number of colours needed to colour the graph. The self-organizing approach is needed to solve scheduling tasks in the applications of ad hoc networks. Nodes in ad hoc networks are usual...

In this paper, we introduce the concept of an intuitionistic fuzzy graph structure (IFGS). We discuss certain notions, including intuitionistic fuzzy Bi-cycles, intuitionistic fuzzy Bi-trees and φ-complement of an intuitionistic fuzzy graph structure with several examples. We also present φ-complement of an intuitionistic fuzzy graph structure along with self-complementary and strong self-compl...

The study of the viewer-centered object representation known as the aspect graph has recently been an active area of research in computer vision. The aspect graph is desirable because it provides a complete enumeration of all possible distinct views of an object, given a particular model for viewpoint space and adefinition of "distinct". This paper presents a history of the evolution of the asp...