Abstract
Intelligent information access systems integrate text mining and content analysis capabilities as a relevant element in an increasing way. In this paper we present our work focused on the integration of text categorization and summarization to improve information access on a specific medical domain, patient clinical records and related scientific documentation, in the framework of two different research projects: SINAMED and ISIS, developed by a consortium of two research groups from two universities, one hospital and one software development firm. SINAMED has a basic research orientation and its goal is to design new text categorization and summarization algorithms based on the utilization of lexical resources in the biomedical domain. ISIS is a R&D project with a more applied and technology-transfer orientation, focused on more direct practical aspects of the utilization in a concrete public health institution.
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References
Aronson, A.R., Mork, J.G., Gay, C.W., Humphrey, S.M., Rogers, W.J.: The NLM Indexing Initiative’s Medical Text Indexer. In: Proceedings of Medinfo, San Francisco (2004)
Maña, M.J., de Buenaga, M., Gómez, J.M.: Multidocument summarization: An added value to clustering in interactive retrieval. ACM TOIS 22(2), 215–241 (2004)
Mostafa, J., Lam, W.: Automatic classification using supervised learning in a medical document filtering application. Information Processing and Management 36(3), 415–444 (2000)
Ribeiro-Neto, B., Laender, A.H.F., De Lima, L.R.: An Experimental Study in Automatically Categorizing Medical Documents. Journal of the American Society for Information Science and Technology 52(5), 391–401 (2001)
Elhadad, N., McKeown, K.R.: Towards generating patient specific summaries of medical articles. In: Proceedings of Automatic Summarization Workshop (NAACL), Pittsburgh, USA (2001)
Johnson, D.B., Zou, Q., Dionisio, J.D., Liu, V.Z., Chu, W.W.: Modeling medical content for automated summarization. Annals of the New York Academy of Sciences 980, 47–58 (2002)
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© 2006 Springer-Verlag Berlin Heidelberg
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de Buenaga, M., Maña, M., Gachet, D., Mata, J. (2006). The SINAMED and ISIS Projects: Applying Text Mining Techniques to Improve Access to a Medical Digital Library. In: Gonzalo, J., Thanos, C., Verdejo, M.F., Carrasco, R.C. (eds) Research and Advanced Technology for Digital Libraries. ECDL 2006. Lecture Notes in Computer Science, vol 4172. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11863878_65
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DOI: https://doi.org/10.1007/11863878_65
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-44636-1
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