Provide an Optimal Model for Finding the Shortest Estimated Paths with Full Graph Coverage

Due to the increasing volume of information in social networks and the web, the need for efficient and fast algorithms for analyzing graph content is felt more than ever. One of the most important operations in a graph is to find the shortest path between two nodes, which can have different applications in routing and communication. Classic algorithms are very slow and computationally expensive, nearly impossible, so algorithms using approximation approaches are often used based on Landmark nodes. In this study, four landmark models are introduced. Using innovative methods, landmark nodes are selected for each nodes cluster, the shortest paths are pre-computed and the results are Hashing for direct access. Hence, a fast, efficient and precise result retrieval is possible when an online query is executed. The proposed methods cover the entire graph can reduce the error rate by 0.0016.