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KMID : 0603720110170010024
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Journal of Korean Society of Medical Informatics
2011 Volume.17 No. 1 p.24 ~ p.28
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Evaluation of Co-occurring Terms in Clinical Doc-uments Using Latent Semantic Indexing
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Han Choong-Hyun
Yoo Soo-Young
Choi Jin-Wook
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Abstract
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Objectives: Measurement of similarities between documents is typically influenced by the sparseness of the term-document matrix employed. Latent semantic indexing (LSI) may improve the results of this type of analysis.
Methods: In this study, LSI was utilized in an attempt to reduce the term vector space of clinical documents and newspaper editorials.
Results: After ap-plying LSI, document similarities were revealed more clearly in clinical documents than editorials. Clinical documents which can be characterized with co-occurring medical terms, various expressions for the same concepts, abbreviations, and typo-graphical errors showed increased improvement with regards to a correlation between co-occurring terms and document similarities.
Conslusions: Our results showed that LSI can be used effectively to measure similarities in clinical documents. In addition, correlation between the co-occurrence of terms and similarities realized in this study is an important positive feature associated with LSI.
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KEYWORD
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Information Storage and Retrieval, Cluster Analysis, Documentation
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