Clustering More than Two Million Biomedical Publications: Comparing the Accuracies of Nine Text-Based Similarity Approaches

BACKGROUND: We investigate the accuracy of different similarity approaches for clustering over two million biomedical documents. Clustering large sets of text documents is important for a variety of information needs and applications such as collection management and navigation, summary and analysis...

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Detalles Bibliográficos
Autores principales: Boyack, Kevin W., Newman, David, Duhon, Russell J., Klavans, Richard, Patek, Michael, Biberstine, Joseph R., Schijvenaars, Bob, Skupin, André, Ma, Nianli, Börner, Katy
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2011
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3060097/
https://www.ncbi.nlm.nih.gov/pubmed/21437291
http://dx.doi.org/10.1371/journal.pone.0018029

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3060097/
https://www.ncbi.nlm.nih.gov/pubmed/21437291
http://dx.doi.org/10.1371/journal.pone.0018029

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