Text Clustering with String Kernels in R

Karatzoglou, Alexandros and Feinerer, Ingo (2006) Text Clustering with String Kernels in R. Research Report Series / Department of Statistics and Mathematics, 34. Department of Statistics and Mathematics, WU Vienna University of Economics and Business, Vienna.


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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)

Item Type: Paper
Additional Information: GfKl 2006, Berlin, Germany
Keywords: text mining / string kernels / spectral clustering / kernel k-means / R / kernlab
Divisions: Departments > Finance, Accounting and Statistics > Statistics and Mathematics
Depositing User: Repository Administrator
Date Deposited: 08 May 2006 20:08
Last Modified: 22 Oct 2019 00:41
URI: https://epub.wu.ac.at/id/eprint/1002


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