Evaluation of Co-occurring Terms in Clinical Documents Using Latent Semantic Indexing

Healthc Inform Res. 2011 Mar;17(1):24-8. doi: 10.4258/hir.2011.17.1.24. Epub 2011 Mar 31.


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 applying 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 typographical errors showed increased improvement with regards to a correlation between co-occurring terms and document similarities.

Conclusions: 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.

Keywords: Cluster Analysis; Documentation; Information Storage and Retrieval.