Building and Maintaining Web Taxonomies
A recognized problem for internet commerce is the task of building a product taxonomy from web pages, without access to corporate databases, and then populating a database with link information about service, spare parts, reviews, product specifications, product family, etc. A key precursor for this task is the ability to build classification hierarchies in an unsupervised manner of web pages potentially useful. However, a nasty aspect of the real world is that most web pages have multiple facets. A web page might contain information about cameras and computers, as well as having both specification and sale data. We are interested in methods for unsupervised learning of multiple facet models which automatically allow these multiple facets to be extracted or predicted from examples. We will present some examples using the Reuters 2000 XML Corpus containing 800,000 Reuters newswires from the year beginning 20th August 1996. Our system, called Ydin, inputs XML/XHTML pages and displays results using a custom web interface. It extracts different facets and provides a navigation tool for investigating the results.