Text Mining
Manas A. Pathak ()
Chapter 8 in Beginning Data Science with R, 2014, pp 137-157 from Springer
Abstract:
Abstract In this chapter we consider the problem of analyzing text data with R. Text is perhaps the most ubiquitous form of data. Analysis of text data has many practical applications including information retrieval, social network analysis, spam filtering, and sentiment analysis.
Keywords: Text Mining; Text Data; Sentiment Analysis; Text Document; Data Frame (search for similar items in EconPapers)
Date: 2014
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-12066-9_8
Ordering information: This item can be ordered from
http://www.springer.com/9783319120669
DOI: 10.1007/978-3-319-12066-9_8
Access Statistics for this chapter
More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().