Exogeneous and Endogeneous Approaches to Semantic Categorization of Unknown Technical Terms

Acquiring and updating terminological resources are di cult and tedious tasks, especially when semantic information should be provided. This paper deals with Term Semantic Categorization. The goal of this process is to assign semantic categories to unknown technical terms. We propose two approaches to the problem that rely on di erent knowledge sources. The exogeneous approach exploits contextual information extracted from corpora. The endogeneous approach relies on a lexical analysis of the technical terms. After describing the two implemented methods, we present the experiments that we conducted on signi cant test sets. The results demonstrate that term categorization can provide a reliable help in the terminology acquisition processes.