Automatic document indexing in large medical collections

Authors:
Angelos Hliaoutakis;Kalliopi Zervanou;Euripides G.M. Petrakis;Evangelos E. Milios
Affiliations:
University of Crete (TUC), Chania, Crete, Greece;University of Crete (TUC), Chania, Crete, Greece;University of Crete (TUC), Chania, Crete, Greece;Dalhousie University, Halifax, Nova Scotia, Canada
Venue:
HIKM '06 Proceedings of the international workshop on Healthcare information and knowledge management
Year:
2006

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Abstract

Term extraction relates to extracting the most characteristic or important terms (words or phrases) in a document. This information is commonly used for improving the accuracy of document indexing and retrieval in large text collections. It also allows for faster and better understanding of the contents of a document collection without first browsing through the contents of its documents. This paper presents AMTEx an automatic term extraction method, specifically designed for the automatic indexing of documents in large medical collections such as MEDLINE, the premier bibliographic database of the U.S. National Library of Medicine (NLM). AMTEx combines MeSH, the terminological thesaurus resource of NLM, with a well-established method for extraction of domain terms, the C/NC-value method. The performance evaluation of various AMTEx configurations in the indexing task is measured against the current state-of-the-art, the MMTx method. The experimental results on a subset of MEDLINE documents demonstrate that AMTEx achieves better precision and recall than MMTx.