Please use this identifier to cite or link to this item: http://ir.inflibnet.ac.in/handle/1944/1856
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dc.contributor.authorEcheverria, Mercedes-
dc.contributor.authorStuart, David-
dc.contributor.authorBlanke, Tobias-
dc.date.accessioned2015-03-11T10:15:02Z-
dc.date.available2015-03-11T10:15:02Z-
dc.date.issued2015-03-12-
dc.identifier.isbn978-93-81232-05-7-
dc.identifier.urihttp://hdl.handle.net/1944/1856-
dc.description.abstractThis paper reports the results obtained on the predictability of references for the identification of derivative articles from doctoral theses, based on a sample of 68 medical theses and 334 articles published by the same theses authors. The study performs an analysis of the common references shared by theses and articles through a text similarity approach. A textual similarity comparison is carried out with the discursive sections of articles (Introduction, Methodology, Results and Discussion) based on the full-text of theses and articles. The results suggest that the Reference section has a high sensitivity to detect true positives cases and a low specificity to identify negative cases, corresponding to a high recall a low precision in the detection of derivative articles.en_US
dc.language.isoen_USen_US
dc.publisherINFLIBNET Centreen_US
dc.subjectDerivative Articlesen_US
dc.subjectDoctoral Thesesen_US
dc.subjectCluster Analysis Methodologyen_US
dc.titlePotential Predictibility of References in the Identification of Derivative Articles from Doctoral Thesesen_US
dc.typeArticleen_US
Appears in Collections:CALIBER 2015: Shimla,HP

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