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Title:
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A KNOWLEDGE MANAGEMENT SYSTEM FOR ORGANIZING MEDLINE DATABASE |
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Author(s):
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Su-shing Chen , Hyunki Kim |
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ISBN:
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978-972-8924-40-9 |
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Editors:
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Jörg Roth, Jairo Gutiérrez and Ajith P. Abraham (series editors: Piet Kommers, Pedro Isaías and Nian-Shing Chen) |
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Year:
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2007 |
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Edition:
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Single |
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Keywords:
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Text categorizatiom, text classificatiom, text mining |
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Type:
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Short Paper |
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First Page:
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182 |
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Last Page:
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186 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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With the explosion of biomedical data, information overload and users inability of expressing their information needs
may become more serious. To solve those problems, this paper presents a text data mining method that uses both text
categorization and text clustering for building concept hierarchies for MEDLINE citations. The approach we propose is a
three-step data mining process for organizing MEDLINE database: (1) categorizations according to MeSH terms, MeSH
major topics, and the co-occurrence of MeSH descriptors; (2) clustering using the results of MeSH term categorization;
and (3) visualization of categories and hierarchical clusters. The hierarchies automatically generated may be used to
support users in browsing behavior and help them identify good starting points for searching. An interface for this
underlying system is also presented. |
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