Incorporating Site-Level Knowledge to Extract Structured Data From Web Forums

Overview

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. This paper, studies the problem of structured data extraction from various web forum sites. The 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 lever-age the knowledge inside an individual page, the paper incorporates both page-level and site-level knowledge and employ Markov Logic Networks (MLNs) to effectively integrate all useful evidence by learning their importance automatically.