Web crawling is a process performed to collect web pages from the web, in order to be indexed and used for displaying the search results according to users' requirements. In addition, web crawlers must continually revisit web pages, to keep the search engine database updated. Moreover, it is fundamental to determine in the crawling process, the most important pages to be recrawled first. This is to avoid the time limitation and network issues that face the web crawling process. Thus, this research attempts to introduce a method that is used to indicate the crawler, specifically, in order to identify in what order it should recrawl web pages that have been crawled before, as to acquire more important and valuable pages earlier than others. In addition, the researchers proposed a web crawling strategy which is based on the topic similarity, accompanied with the dynamicity of web pages, where the crawler was downloading relevant pages and recrawling them recursively. Also, every time a change emerged in one of the pages, its counter increased. Therefore, if the page was relevant and changed frequently it would be considered an important page and was given a high priority in the crawling process. The obtained results indicated that using web pages' dynamicity is an effective way for prioritising web pages in the crawling process, in order to obtain the highest dynamic pages first, as there is a high possibility of being changed in terms of their content, before the least dynamic ones.