A service provided by the WU Library and the WU IT-Services

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.

[img]
Preview
PDF
Download (217Kb) | Preview

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)

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 22:08
Last Modified: 06 Jun 2015 17:12
URI: http://epub.wu.ac.at/id/eprint/1002

Actions

View Item