Paper Title
Multilevel Approach and Label on Graph Partitioning

Abstract
The growing relevance of graph data in numerous sectors necessitates the efficient processing of large-scale graph data. Furthermore, for parallel/distributed graph processing, well-balanced graph partitioning is essential. The purpose of graph partitioning is to create a well-balanced graph topology with a balanced size of each division and a minimized number of edge cuts. In this paper, we will see one of the efficient partitioning approach that guarantees great edge cutting quality and parallel processing performance base on label propagation method and their impact using the multilevel partitioning method. Keywords - Graph Data, Large-Scale Graph, Graph Partitioning, Label Propagation, Multilevel Partitioning Method.