Kernel-based machine learning for fast text mining in R

Authors:
Alexandros Karatzoglou;Ingo Feinerer
Affiliations:
LITIS, INSA de Rouen, Avenue de Université, 76801 Saint-Etienne du Rouvray, France;Database and Artificial Intelligence Group, Institute of Information Systems, Vienna University of Technology, Austria
Venue:
Computational Statistics & Data Analysis
Year:
2010

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Abstract

Recent advances in the field of kernel-based machine learning methods allow fast processing of text using string kernels utilizing suffix arrays. kernlab provides both kernel methods' infrastructure and a large collection of already implemented algorithms and includes an implementation of suffix-array-based string kernels. Along with the use of the text mining infrastructure provided by tm these packages provide R with functionality in processing, visualizing and grouping large collections of text data using kernel methods. The emphasis is on the performance of various types of string kernels at these tasks.