Text Clustering with String Kernels in R

Alexandros Karatzoglou, Ingo Feinerer

Publication: Working/Discussion PaperWU Working Paper

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Abstract

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)
Original languageEnglish
Place of PublicationVienna
PublisherDepartment of Statistics and Mathematics, WU Vienna University of Economics and Business
Publication statusPublished - 2006

Publication series

NameResearch Report Series / Department of Statistics and Mathematics
No.34

WU Working Paper Series

  • Research Report Series / Department of Statistics and Mathematics

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