Web Template Extraction Based on Hyperlink Analysis
This addresses a domain-specific problem for web crawlers and indexers by improving efficiency in processing web data, though it appears incremental as it builds on existing template extraction techniques.
The paper tackles the problem of web templates containing irrelevant information like ads and menus, which waste resources for crawlers and indexers, by proposing a novel method for automatic template extraction based on similarity analysis of DOM trees using menus information, with experiments showing its usefulness.
Web templates are one of the main development resources for website engineers. Templates allow them to increase productivity by plugin content into already formatted and prepared pagelets. For the final user templates are also useful, because they provide uniformity and a common look and feel for all webpages. However, from the point of view of crawlers and indexers, templates are an important problem, because templates usually contain irrelevant information such as advertisements, menus, and banners. Processing and storing this information is likely to lead to a waste of resources (storage space, bandwidth, etc.). It has been measured that templates represent between 40% and 50% of data on the Web. Therefore, identifying templates is essential for indexing tasks. In this work we propose a novel method for automatic template extraction that is based on similarity analysis between the DOM trees of a collection of webpages that are detected using menus information. Our implementation and experiments demonstrate the usefulness of the technique.