A tm Plug-In for Distributed Text Mining in R

Theußl, Stefan and Feinerer, Ingo and Hornik, Kurt ORCID: https://orcid.org/0000-0003-4198-9911 (2012) A tm Plug-In for Distributed Text Mining in R. Journal of Statistical Software, 51 (5). ISSN 1548-7660


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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 signifficant size.

Item Type: Article
Keywords: text mining / MapReduce / distributed computing / Hadoop
Divisions: Departments > Finance, Accounting and Statistics > Statistics and Mathematics > Hornik
Version of the Document: Published
Depositing User: ePub Administrator
Date Deposited: 26 Sep 2013 13:12
Last Modified: 13 Sep 2021 15:47
FIDES Link: https://bach.wu.ac.at/d/research/results/59097/
URI: https://epub.wu.ac.at/id/eprint/3974


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