LESSONS LEARNED FROM APPLYING AI TO THE WEB

Abstract

Ontobroker applies Artificial Intelligence techniques to improve access to heterogeneous, distributed and semi-structured information sources as they are presented in the World Wide Web or organization-wide 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.