Text Mining Infrastructure in<i>R</i>
Инфраструктура интеллектуального анализа текстов в R
2008-01-01
SCID: 54.1/ny4strjq
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R packagecount-based analysistext classificationtext clusteringtext mining
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Abstract (AI)
During the last decade text mining has become a widely used discipline utilizing statistical and machine learning methods. We present the <strong>tm</strong> package which provides a framework for text mining applications within R. We give a survey on text mining facilities in R and explain how typical application tasks can be carried out using our framework. We present techniques for count-based analysis methods, text clustering, text classification and string kernels.
Key Findings
1
The framework supports count-based text analysis, text clustering, text classification, and string-kernel methods.
2
The package is designed to support statistical and machine-learning approaches to text mining within R.
3
The paper surveys text-mining facilities available in R and demonstrates how typical application tasks can be performed.
4
The tm package provides an R framework for developing and applying text-mining applications.
Research Object
tm package framework for text mining applications within R
Research Subject
Text mining facilities and application tasks, including count-based analysis, text clustering, text classification, and string kernels
Publication Details
Publication Date
2008-01-01
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