Spectral Clustering And Community Detection In
Document Networks
Author(s)
C. K. dos Santos, A. G. Evsukoff & B. S. L. P. de Lima
Abstract
Document clustering is one of the most active research topics in text mining. In
this work two approaches issued from very different fields are explored for
document clustering: spectral clustering and community detection in complex
networks. Both approaches are based on a representation of the document
collection as a graph, of which the nodes represent the documents and the edges
represent the similarities between each pair of documents, such that the two
approaches have many issues in common. The results of the application of these
two types of techniques to benchmark text mining problems show that they are
complementary and are useful for finding structure in large collections of
documents
Keywords: text mining, document clustering, spectral clustering, community
detection, complex networks, modularity.
Keywords
text mining, document clustering, spectral clustering, community
detection, complex networks, modularity.
Related Book
Other papers in this volume
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