(untitled) (Journal of Pure and Applied Sciences (Science Forum), 2026)
The rapid growth and the dynamic nature of the web have continued to bring chal lenges to the PageRank algorithm. The PageRank algorithm remains the best ranking criteria so far. Many researchers have worked to accelerate PageRank computation, but these two challenges still remain an issue. We propose a model architecture that optimizes the dynamic nature of ant colony optimization to prune the cones of graph nodes and retrieve relevant nodes for users’ display. The potential benefit of our pro posed design indicates an improvement over the traditional PageRank in case of its computation cost and efficiency.