Extracting Context To Improve Accuracy For HTML Content Extraction

Web pages contain clutter (such as ads, unnecessary images and extraneous links) around the body of an article, which distracts a user from actual content. Extraction of 'useful and relevant' content from web pages has many applications, including cell phone and PDA browsing, speech rendering for the visually impaired, reducing noise for information retrieval systems and to generally improve the web browsing experience. In our previous work [16], we developed a framework that employed an easily extensible set of techniques that incorporated results from our earlier work on content extraction [16]. Our insight was to work with DOM trees, rather than raw HTML markup. We present here filters that reduce human involvement in applying heuristic settings for websites and instead automate the job by detecting and utilizing the physical layout and content genre of a given website. We also present work we have done towards improving the usability and performance of our content extraction proxy as well as the quality and accuracy of the heuristics that act as filters for inferring the context of a webpage