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Concept Mining for Indexing Medical Literature

  • Conference paper
Machine Learning and Data Mining in Pattern Recognition (MLDM 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3587))

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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Author information

Authors and Affiliations

  1. University of Washington, 1900 Commerce Street, Box 358426, Tacoma, WA, 98402, USA

    Isabelle Bichindaritz & Sarada Akkineni

Authors
  1. Isabelle Bichindaritz
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  2. Sarada Akkineni
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Editor information

Editors and Affiliations

  1. Institute of Computer Vision and applied Computer Sciences, IBaI, Germany

    Petra Perner

  2. Institute of Media and Information Technology, Chiba University, Japan

    Atsushi Imiya

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© 2005 Springer-Verlag Berlin Heidelberg

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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

  • Online ISBN: 978-3-540-31891-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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