Open AccessRetro: concept-based clustering of biomedical topical sets
Author(s) -
Lana Yeganova,
Won Bae Kim,
Sun Kim,
W. John Wilbur
Publication year - 2014
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btu514
Subject(s) - cluster analysis , computer science , document clustering , data mining , fuzzy clustering , latent dirichlet allocation , information retrieval , snippet , artificial intelligence , machine learning , topic model
Clustering methods can be useful for automatically grouping documents into meaningful clusters, improving human comprehension of a document collection. Although there are clustering algorithms that can achieve the goal for relatively large document collections, they do not always work well for small and homogenous datasets.
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