Reading Between the Lines: Using SHOE to Discover Implicit Knowledge from the Web

Jeff Heflin, James Hendler, and Sean Luke

This paper describes how SHOE, a set of Simple HTML Ontological Extensions, can be used to discover implicit knowledge from the World-Wide Web (WWW). SHOE allows authors to annotate their pages with ontology-based knowledge about page contents. In previous papers, we discussed how the semantic knowledge provided by SHOE allows users to issue queries that are much more sophisticated than keyword search techniques, including queries that require retrieval of information from many sources. Here, we expand upon this idea by describing how SHOE’s ontologies allow agents to understand more than what is explicitly stated in Web pages through the use of context, inheritance, and inference. We use examples to illustrate the usefulness of these features to Web agents and query engines.

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