Researchers in artificial intelligence first developed ontologies to facilitate knowledge sharing and reuse. Since the beginning of the 1990s, ontologies have become a popular research topic, and several AI research communities—including Ontologies play a major role in supporting information exchange across various networks. A prerequisite for such a role is the development of a joint standard for specifying and exchanging ontologies. The authors present OIL, a proposal for

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In this article we describe results of our research on the disambiguation of user queries using ontologies for categorization. We present an approach to cluster search results by using classes or "Sense Folders" (prototype categories) derived from the concepts of an assigned ontology, in our case WordNet. Using the semantic relations provided from such a resource, we can assign categories to prior, not annotated documents. The disambiguation of query terms in documents with respect to a user-specific ontology is an important issue in order to improve the retrieval performance for the user. Furthermore, we show that a clustering process can enhance the semantic classification of documents, and we discuss how this clustering process can be further enhanced using only the most descriptive classes of the ontology.