用于信息检索的多术语超级概念评估。
Evaluation of multi-terminology super-concepts for information retrieval.
作者信息
Griffon Nicolas, Soualmia Lina F, Névéol Aurélie, Massari Philippe, Thirion Benoit, Dahamna Badisse, Darmoni Stefan J
机构信息
CISMeF, Rouen University Hospital, France.
出版信息
Stud Health Technol Inform. 2011;169:492-6.
BACKGROUND
Following a recent change in the indexing policy for French quality controlled health gateway CISMeF, multiple terminologies are now being used for indexing in addition to MeSH®.
OBJECTIVE
To evaluate precision and recall of super-concepts for information retrieval in a multi-terminology paradigm compared to MeSH-only.
METHODS
We evaluate the relevance of resources retrieved by multi-terminology super-concepts and MeSH-only super-concepts queries.
RESULTS
Recall was 8-14% higher for multi-terminology super-concepts compared to MeSH only super-concepts. Precision decreased from 0.66 for MeSH only super-concepts to 0.61 for multi-terminology super-concepts. Retrieval performance was found to vary significantly depending on the super-concepts (p<10) and indexing methods (manual vs automatic; p<0.004).
CONCLUSION
A multi-terminology paradigm contributes to increase recall but lowers precision. Automated tools for indexing are not accurate enough to allow a very precise information retrieval.
背景
随着法国质量控制健康网关CISMeF索引政策最近的变化，除医学主题词表（MeSH®）外，现在还使用多种术语进行索引。
目的
与仅使用MeSH相比，评估在多术语范式中用于信息检索的超级概念的精确率和召回率。
方法
我们评估通过多术语超级概念和仅MeSH超级概念查询检索到的资源的相关性。
结果
与仅使用MeSH超级概念相比，多术语超级概念的召回率高8 - 14%。精确率从仅使用MeSH超级概念的0.66降至多术语超级概念的0.61。发现检索性能因超级概念（p<10）和索引方法（手动与自动；p<0.004）而有显著差异。
结论
多术语范式有助于提高召回率，但降低了精确率。用于索引的自动化工具不够准确，无法实现非常精确的信息检索。
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