Medical Document Indexing and Retrieval: AMTEx vs. NLM MMTx
Angelos Hliaoutakis, Kalliopi Zervanou, Euripides G. M. Petrakis
Abstract
Angelos Hliaoutakis, Kalliopi Zervanou, Euripides G. M. Petrakis
Abstract
AMTEx is a medical document indexing 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 wellestablished method for term extraction, the C/NC-value method. The performance evaluation of two AMTEx configurations is measured against the current state-of-theart, the MMTx method in indexing and retrieval tasks in three experiments. In the first, a subset of MEDLINE (PMC) full document corpus was used for the indexing task. In the second and third, a subset of MEDLINE (OHSUMED) abstracts was used for indexing and retrieval respectively. The experimental results demonstrate that AMTEx achieves better precision in all tasks, in 50-20 % of the processing time compared to MMTx.
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AMTEx is a medical document indexing 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 wellestablished method for term extraction, the C/NC-value method. The performance evaluation of two AMTEx configurations is measured against the current state-of-theart, the MMTx method in indexing and retrieval tasks in three experiments. In the first, a subset of MEDLINE (PMC) full document corpus was used for the indexing task. In the second and third, a subset of MEDLINE (OHSUMED) abstracts was used for indexing and retrieval respectively. The experimental results demonstrate that AMTEx achieves better precision in all tasks, in 50-20 % of the processing time compared to MMTx.
Key concepts: Search engine indexing, Information retrieval, Computer science, National library, Automatic indexing, Thesaurus, Document retrieval, MEDLINE