document: Joint optimization of wrapper generation and template detection Many websites have large collections of pages generated dynamically from an underlying structured source like a database . The data of a category are typically encoded into similar pages by a common script or template . In recent years , some value-added services , such as comparison shopping and vertical search in a specific domain , have motivated the research of extraction technologies with high accuracy . Almost all previous works assume that input pages of a wrapper induction system conform to a common template and they can be easily identified in terms of a common schema of URL . However , we observed that it is hard to distinguish different templates using dynamic URLs today . Moreover , since extraction accuracy heavily depends on how consistent input pages are , we argue that it is risky to determine whether pages share a common template solely based on URLs . Instead , we propose a new approach that utilizes similarity between pages to detect templates . Our approach separates pages with notable inner differences and then generates wrappers , respectively . Experimental results show that our proposed approach is feasible and effective for improving extraction accuracy .
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