000			01407cam a22002057i 4500
020			_a9781491981627
020			_a9789352135769
082	0	4	_a006.35 _bSIL
100	1		_aSilge, Julia,
245	1	0	_aText mining with R : a tidy approach
250			_aFirst edition.
260			_aMumbai : _bShroff Publishers, _c2017
300			_axii, 178 pages : _billustrations ;
500			_aOriginally published in Sebastopol, CA. by O'Reilly Media,
520			_aMuch of the data available today is unstructured and text-heavy, making it challenging for analysts to apply their usual data wrangling and visualization tools. With this practical book, you’ll explore text-mining techniques with tidytext, a package that authors Julia Silge and David Robinson developed using the tidy principles behind R packages like ggraph and dplyr. You’ll learn how tidytext and other tidy tools in R can make text analysis easier and more effective. The authors demonstrate how treating text as data frames enables you to manipulate, summarize, and visualize characteristics of text. You’ll also learn how to integrate natural language processing (NLP) into effective workflows. Practical code examples and data explorations will help you generate real insights from literature, news, and social media
650		0	_aR (Computer program language)
650		0	_aData mining.
700	1		_aRobinson, David
942			_cBK
999			_c44325 _d44325