Source:http://linkedlifedata.com/resource/pubmed/id/16138542
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| Predicate | Object |
|---|---|
| rdf:type | |
| lifeskim:mentions | |
| pubmed:issue |
2
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| pubmed:dateCreated |
2005-9-5
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| pubmed:abstractText |
The ability to perform an exploratory search and retrieval of relevant documents from a large collection of domain-specific documents is an important requirement both in the field of medicine and other areas. In this paper, we present a unsupervised distributional clustering technique called SOPHIA. SOPHIA provides a semantically meaningful visual clustering of the document corpus in conjunction with an intuitive interactive search facility. We assess the effectiveness of SOPHIA's cluster-based information retrieval for the MEDLINE testset collection known as OHSUMED.
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| pubmed:language |
eng
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| pubmed:journal | |
| pubmed:citationSubset |
IM
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| pubmed:status |
MEDLINE
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| pubmed:month |
Jun
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| pubmed:issn |
1089-7771
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| pubmed:author | |
| pubmed:issnType |
Print
|
| pubmed:volume |
9
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| pubmed:owner |
NLM
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| pubmed:authorsComplete |
Y
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| pubmed:pagination |
256-65
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| pubmed:meshHeading | |
| pubmed:year |
2005
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| pubmed:articleTitle |
SOPHIA: an interactive cluster-based retrieval system for the OHSUMED collection.
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| pubmed:affiliation |
Department of Programming Technology, Saint Petersburg State University, St. Petersburg, Russia. vdobr@oasis.apmath.spbu.ru
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| pubmed:publicationType |
Journal Article
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