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Text Clustering with String Kernels in R

We present a package which provides a general framework, including tools and algorithms, for text mining in R using the S4 class system. Using this package and the kernlab R package we explore the use of kernel methods for clustering (e.g., kernel k-means and spectral clustering) on a set of text documents, using string kernels. We compare these methods to a more traditional clustering technique like k-means on a bag of word representation of the text and evaluate the viability of kernel-based methods as a text clustering technique. (author's abstract) / Series: Research Report Series / Department of Statistics and Mathematics

Identiferoai:union.ndltd.org:VIENNA/oai:epub.wu-wien.ac.at:epub-wu-01_96d
Date January 2006
CreatorsKaratzoglou, Alexandros, Feinerer, Ingo
PublisherDepartment of Statistics and Mathematics, WU Vienna University of Economics and Business
Source SetsWirtschaftsuniversität Wien
LanguageEnglish
Detected LanguageEnglish
TypePaper, NonPeerReviewed
Formatapplication/pdf
Relationhttp://epub.wu.ac.at/1002/

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