krishnaharsha/BullsEyeR: Topic Modelling for content curation @COGNIZANT ANALYTICS

1)Helps in intial preprocessing like converting text to lower case, removing (punctuation, numbers,stop words), stemming, sparsity control and TF-IDF pre-processing.2) Helps in recognizing domain/corpus specific stop words 3) makes use of 'ldatunig' output to pick optimal number of topics for LDA modelling 4) Helps in extracting dominant words or key words that represent the context/topics of the content in each document.

Getting started

Package details

AuthorKrishna Harsha @COGNIZANT ANALYTICS
MaintainerKrishna [email protected] ANALYTICS <[email protected]>
LicenseGPL
Version0.1.0
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("devtools")
library(devtools)
install_github("krishnaharsha/BullsEyeR")
krishnaharsha/BullsEyeR documentation built on Dec. 5, 2017, 12:33 a.m.