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Authors: Stefan Theuβl, Ingo Feinerer, Kurt Hornik
Title: [download]
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A tm Plug-In for Distributed Text Mining in R
Reference: Vol. 51, Issue 5, Nov 2012
Submitted 2011-03-16, Accepted 2012-11-02
Type: Article
Abstract:

R has gained explicit text mining support with the tm package enabling statisticians to answer many interesting research questions via statistical analysis or modeling of (text) corpora. However, we typically face two challenges when analyzing large corpora: (1) the amount of data to be processed in a single machine is usually limited by the available main memory (i.e., RAM), and (2) the more data to be analyzed the higher the need for efficient procedures for calculating valuable results. Fortunately, adequate programming models like MapReduce facilitate parallelization of text mining tasks and allow for processing data sets beyond what would fit into memory by using a distributed file system possibly spanning over several machines, e.g., in a cluster of workstations. In this paper we present a plug-in package to tm called tm.plugin.dc implementing a distributed corpus class which can take advantage of the Hadoop MapReduce library for large scale text mining tasks. We show on the basis of an application in culturomics that we can efficiently handle data sets of significant size.

Paper: [download]
(7050)
A tm Plug-In for Distributed Text Mining in R
(application/pdf, 402.1 KB)
Supplements: [download]
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tm.plugin.dc_0.2-4.tar.gz: R source package
(application/x-gzip, 7.3 KB)
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(336)
v51i05.R: R example code from the paper
(application/octet-stream, 7.1 KB)
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Downloading_data.txt Instructions for downloading data set.
(text/plain, 200 Bytes)
Resources: BibTeX | OAI
Creative Commons License
This work is licensed under the licenses
Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3)
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