MedEvi: retrieving textual evidence of relations between biomedical concepts from Medline.
MedEvi: retrieving textual evidence of relations between biomedical concepts from Medline.
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DOI：
10.1093/bioinformatics/btn117
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发表时间：
2008-06-01
期刊：
影响因子：
--
通讯作者：
Rebholz-Schuhmann D
中科院分区：
文献类型：
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作者：
Kim JJ;Pezik P;Rebholz-Schuhmann D
摘要：运行在MEDLINE摘要上的搜索引擎已被生物学家广泛用于查找与其研究相关的出版物。然而，现有的搜索引擎，如PubMed，有局限性时，应用于寻找给定概念之间的关系的文本证据的任务。这些局限性主要是由于搜索引擎不能有效地处理可能隐含术语之间的语义关系的多术语查询的问题。为了解决这个问题，我们提出了MedEvi，一种新的搜索引擎，它对匹配多项查询的出现施加位置限制，根据观察，在文本中明确说明的语义关系的术语不会发现彼此太远。MedEvi还从匹配事件的局部上下文中识别出具有生物学和统计学意义的其他关键词，以帮助用户重新制定他们的查询以获得更好的结果。可用性：http://www.ebi.ac.uk/tc-test/textmining/medevi/联系人：kim@ebi.ac.uk
Summary: Search engines running on MEDLINE abstracts have been widely used by biologists to find publications that are related to their research. The existing search engines such as PubMed, however, have limitations when applied for the task of seeking textual evidence of relations between given concepts. The limitations are mainly due to the problem that the search engines do not effectively deal with multi-term queries which may imply semantic relations between the terms. To address this problem, we present MedEvi, a novel search engine that imposes positional restriction on occurrences matching multi-term queries, based on the observation that terms with semantic relations which are explicitly stated in text are not found too far from each other. MedEvi further identifies additional keywords of biological and statistical significance from local context of matching occurrences in order to help users reformulate their queries for better results. Availability: http://www.ebi.ac.uk/tc-test/textmining/medevi/ Contact: kim@ebi.ac.uk
影响因子：
5.8
作者：
Rebholz-Schuhmann, Dietrich;Kirsch, Harald;Stoehr, Peter
通讯作者：
Stoehr, Peter
影响因子：
5.8
作者：
Hoffmann, R;Valencia, A
通讯作者：
Valencia, A