Lessons Learned from Applying AI to the Web

Ontobroker applies Artificial Intelligence techniques to improve access to heterogeneous, distributed and semistructured information sources as they are presented in the World Wide Web or organizationwide intranets. It relies on the use of ontologies to annotate web pages, formulate queries and derive answers. In this paper we will briefly sketch Ontobroker. Then we will discuss its main shortcomings, i.e. we will share the lessons we learned from our exercise. We will also show how On2broker overcomes these limitations. Most important is the separation of the query and inference engines and the integration of new web standards like XML and RDF.

• Type: Journal
• Year: 2000
• Where: IJCIS
• Authors: Dieter Fensel, Jürgen Angele, Stefan Decker, Michael Erdmann, Hans-Peter Schnurr, Rudi Studer, Andreas Witt
• Keywords: Artificial Intelligence, IJCIS 2000, Organizationwide Intranets, World Wide Web