document: Incorporating site-level knowledge to extract structured data from web forums Web forums have become an important data resource for many web applications , but extracting structured data from unstructured web forum pages is still a challenging task due to both complex page layout designs and unrestricted user created posts . In this paper , we study the problem of structured data extraction from various web forum sites . Our target is to find a solution as general as possible to extract structured data , such as post title , post author , post time , and post content from any forum site . In contrast to most existing information extraction methods , which only leverage the knowledge inside an individual page , we incorporate both page-level and site-level knowledge and employ Markov logic networks ( MLNs ) to effectively integrate all useful evidence by learning their importance automatically . Site-level knowledge includes ( 1 ) the linkages among different object pages , such as list pages and post pages , and ( 2 ) the interrelationships of pages belonging to the same object . The experimental results on 20 forums show a very encouraging information extraction performance , and demonstrate the ability of the proposed approach on various forums . We also show that the performance is limited if only page-level knowledge is used , while when incorporating the site-level knowledge both precision and recall can be significantly improved .
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