Vertical search engines use focused crawlers as their key component and develop some specific algorithms to select Web pages relevant to some pre-defined set of topics. Therefore, how to effectively build up a semantic pattern for specific topics is extremely important to such search engines. In this paper we propose an UBFC (URL rule based focused crawler) algorithm based on a double-crawler framework (an experimental crawler and a focused crawler). The kernel of our UBFC is an URL regular expression learner, which is used to automatically learn and generalize the regular expressions of URLs of the sample Web pages. The so generated URL regular expressions are used to direct the UBFC to work. Using UBFC, we developed a Nutch based focused crawler for hardwaretoday.com and get an excellent result. To evaluate the UBFC, we conduct some experiments to make an analysis through comparison with two proposed methods, the BFSC (breadth first search crawler) and BLFC (baseline focused crawler).