Package: BullsEyeR
Type: Package
Title: Topic Modelling
Version: 0.2.0
Date: 2017-12-11
Author: Krishna Harsha
Maintainer: Krishna Harsha <khkrishnaharsha123@gmail.com>
Depends: tm, NLP, topicmodels, Matrix, slam
Description: Helps in initial processing like converting text to lower case, removing punctuation, numbers, stop words, stemming, sparsity control and term frequency inverse document frequency processing. Helps in recognizing domain or corpus specific stop words. Makes use of 'ldatunig' output to pick optimal number of topics for topic modelling. Helps in topic modelling the content. 
License: GPL
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-12-21 11:06:37 UTC; 619036
Repository: CRAN
Date/Publication: 2017-12-21 11:15:41 UTC
Built: R 4.0.0; ; 2020-04-10 04:10:53 UTC; windows
