Abstract. Advertising on the World Wide Web is based around automatically matching web pages with appropriate advertisements, in the form of banner ads, interactive adverts, or text links. Traditionally this has been done by manual classification of pages, or more recently using information retrieval techniques to find the most important keywords from the page, and match these to keywords being used by adverts. In this paper, we propose a new model for online advertising, based around lightweight embedded semantics. This will improve the relevancy of adverts on the World Wide Web and help to kick-start the use of RDFa as a mechanism for adding lightweight semantic attributes to the Web. Furthermore, we propose a system architecture for the proposed new model, based on our scalable ontology reasoning infrastructure TrOWL.
Edward Thomas, Jeff Z. Pan, Stuart Taylor, Yuan Re