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BTM
View on CRAN: Click
here
Download and install BTM package within the R console
Install from CRAN:
install.packages("BTM")
Install from Github:
library("remotes")
install_github("cran/BTM")
Install by package version:
library("remotes")
install_version("BTM", "0.3.7")
Attach the package and use:
library("BTM")
Maintained by
Jan Wijffels
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-05-31
Latest Update: 2023-02-11
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) .
How to cite:
Jan Wijffels (2019). BTM: Biterm Topic Models for Short Text. R package version 0.3.7, https://cran.r-project.org/web/packages/BTM
Previous versions and publish date:
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Other R packages that BTM depends,
imports, suggests or enhances
Functions, R codes and Examples using
the BTM R package
Some associated functions: BTM . logLik.BTM . predict.BTM . terms.BTM . terms.data.frame .
Some associated R codes: RcppExports.R . btm.R . pkg.R . Full BTM package functions and examples
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