DESCRIPTION

Package: BTM
Type: Package
Title: Biterm Topic Models for Short Text
Version: 0.3.7
Maintainer: Jan Wijffels <jwijffels@bnosac.be>
Authors@R: c(
    person('Jan', 'Wijffels', role = c('aut', 'cre', 'cph'), email = 'jwijffels@bnosac.be', comment = "R wrapper"), 
    person('BNOSAC', role = 'cph', comment = "R wrapper"), 
    person('Xiaohui Yan', role = c('ctb', 'cph'), email = 'xhcloud@gmail.com', comment = "BTM C++ library"))
Description: Biterm Topic Models find topics in collections of short texts. 
    It is a word co-occurrence based topic model that learns topics by modeling word-word co-occurrences patterns which are called biterms.
    This in contrast to traditional topic models like Latent Dirichlet Allocation and Probabilistic Latent Semantic Analysis 
    which are word-document co-occurrence topic models.
    A biterm consists of two words co-occurring in the same short text window.  
    This context window can for example be a twitter message, a short answer on a survey, a sentence of a text or a document identifier. 
    The techniques are explained in detail in the paper 'A Biterm Topic Model For Short Text' by Xiaohui Yan, Jiafeng Guo, Yanyan Lan, Xueqi Cheng (2013) <https://github.com/xiaohuiyan/xiaohuiyan.github.io/blob/master/paper/BTM-WWW13.pdf>.
License: Apache License 2.0
URL: https://github.com/bnosac/BTM
Encoding: UTF-8
Imports: Rcpp, utils
Suggests: udpipe, data.table
LinkingTo: Rcpp
RoxygenNote: 7.1.2