A substantial fraction of the Web consists of pages that are dynamically generated using a common template populated with data from databases, such as product description pages on e-commerce sites. The objective of the proposed research is to automatically detect the template behind these pages and extract embedded data (e.g., product name, price...). The template detection problem is formalized and an analysis of the underlying structure of template-generated pages is made. A template detection approach is presented and the detected templates are used to extract data from instance pages. Comparing with many other existing work, the approach is applicable for both "list pages" and "detail pages". Experimental results on two large third-party test beds show that the approach can achieve high extraction accuracy.