Ontologically Supported Semantic Matching

Evaluation of the closeness of two texts is a subtask for F T R and I R systems. The basic means used to accomplish it is the matching of a to m ic te x t e n t i t ie s (ATEs) such as words, stems, simple phrases and/or concepts. We address the question how concepts can be used as ATEs more efficiently in order to match “s m a l l d u c k ” with “s m a l l b ir d ”. The o n to -m a tc h in g technique introduced in the paper makes extensive use of lexical ontologies similar to WordNet. We work with two tasks in mind: query expansion and text concept indexing. We outline some arguments showing why onto-matching is useful and how it can be implemented. Also, we conducted some experiments with query expansion for AltaVista.