Conceptual document indexing using a large scale semantic dictionary providing a concept hierarchy

Automatic indexing is one of the important technologies used for Textual Data Analysis applications. Standard document indexing techniques usually identify the most relevant keywords in the documents. This paper presents an alternative approach that aims at performing document indexing by associating concepts with the document to index instead of extracting keywords out of it. The concepts are extracted out of the EDR Electronic Dictionary that provides a concept hierarchy based on hyponym/hypernym relations. An experimental evaluation based on a probabilistic model was performed on a sample of the INSPEC bibliographic database and we present the promising results that were obtained during the evaluation experiments.