Abstract
This article addresses the task of mining concepts from biomedical literature to index and search through this documents base. This research takes place within the Telemakus project, which has for goal to support and facilitate the knowledge discovery process by providing retrieval, visual, and interaction tools to mine and map research findings from research literature in the field of aging. A concept mining component automating research findings extraction such as the one presented here, would permit Telemakus to be efficiently applied to other domains. The main principle that has been followed in this project has been to mine from the legends of the documents the research findings as relationships between concepts from the medical literature. The concept mining proceeds through stages of syntactic analysis, semantic analysis, relationships building, and ranking.
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Bichindaritz, I., Akkineni, S. (2005). Concept Mining for Indexing Medical Literature. In: Perner, P., Imiya, A. (eds) Machine Learning and Data Mining in Pattern Recognition. MLDM 2005. Lecture Notes in Computer Science(), vol 3587. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11510888_68
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DOI: https://doi.org/10.1007/11510888_68
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26923-6
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