Your browser doesn't support javascript.
loading
Evaluation of Co-occurring Terms in Clinical Documents Using Latent Semantic Indexing / 대한의료정보학회지
Healthcare Informatics Research ; : 24-28, 2011.
Article in English | WPRIM | ID: wpr-106942
ABSTRACT

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.
Subject(s)

Full text: Available Index: WPRIM (Western Pacific) Main subject: Semantics / Cluster Analysis / Information Storage and Retrieval / Periodical / Abstracting and Indexing Language: English Journal: Healthcare Informatics Research Year: 2011 Type: Article

Similar

MEDLINE

...
LILACS

LIS

Full text: Available Index: WPRIM (Western Pacific) Main subject: Semantics / Cluster Analysis / Information Storage and Retrieval / Periodical / Abstracting and Indexing Language: English Journal: Healthcare Informatics Research Year: 2011 Type: Article