Research Projects

This proposal focuses on the graph clustering problem, a crucial step in large-scale data processing. It aims to study data represented as graphs, mainly from web and social network graphs. The main goal is to divide the graph into subgraphs that satisfy certain graph-theoretic properties, such as sparseness, perfect matching, and q-colorability. The proposal aims to explore properties such as shallow minor freeness, perfect matching, and q-colorability. The project aims to start a new direction in graph clustering research by examining the properties of each subgraph, aiming to improve the efficiency of data processing.