The two significant tasks of a focused Web crawler are finding relevant documents and prioritizing them for effective download. For the first task, we propose an algorithm to fetch and analyze the most effective HTML elements of the page to predict and elicit the topical focus of each unvisited page with high accuracy. For the second task, we propose a scoring function of the relevant URLs through the use of T-Graph to prioritize each unvisited link. Thus, our novel method uniquely combines these approaches, giving precision and recall values close to 50%, which indicate the significance of the proposed architecture. 
A focused crawler combinatory link and content model based on T-Graph principles