The requirement of a web Crawler that downloads most relevant pages is still a major challenge in the field of Information Retrieval Systems. The use of link analysis algorithms like page rank and other Importance-metrics have shed a new approach in prioritizing the URL queue for downloading higher relevant pages. In this paper, the combination of these metrics along with a new metric called association-metric has been proposed. The association-metric estimates the semantic content of the URL based on the domain dependent ontology, which in turn strengthens the metric that is used for prioritizing the URL queue. In addition, after downloading the page, the association metric plays important role in estimating the relevancy of the links in that page. The proposed new metric will solve the major problem of finding the relevancy of the pages before the process of crawling, to an optimal level.