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author | Lars-Dominik Braun <ldb@leibniz-psychology.org> | 2021-03-15 10:49:50 +0100 |
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committer | Lars-Dominik Braun <ldb@leibniz-psychology.org> | 2021-03-15 10:53:21 +0100 |
commit | ca3913d1f8d0582236989e516dc61ed38eec6ed9 (patch) | |
tree | a7a70e98d9b5b43c0d1fc1f3ee988700a2364d49 | |
parent | 20fb147c9abbd60bea1c8d9e54b11b2b95e69970 (diff) | |
download | guix-ca3913d1f8d0582236989e516dc61ed38eec6ed9.tar.gz guix-ca3913d1f8d0582236989e516dc61ed38eec6ed9.zip |
gnu: Add r-btm.
* gnu/packages/cran.scm (r-btm): New variable.
-rw-r--r-- | gnu/packages/cran.scm | 31 |
1 files changed, 31 insertions, 0 deletions
diff --git a/gnu/packages/cran.scm b/gnu/packages/cran.scm index 66fd2c733d..91cf7c550d 100644 --- a/gnu/packages/cran.scm +++ b/gnu/packages/cran.scm @@ -28045,3 +28045,34 @@ Application Program Interfaces (API)}.") "Imports plain-text ASC data files from EyeLink eye trackers into (relatively) tidy data frames for analysis and visualization.") (license license:gpl3))) + +(define-public r-btm + (package + (name "r-btm") + (version "0.3.5") + (source + (origin + (method url-fetch) + (uri (cran-uri "BTM" version)) + (sha256 + (base32 + "1x6bncb7r97z8bdyxnn2frdi9kyawfy6c2041mv9f42zdrfzm6jb")))) + (properties `((upstream-name . "BTM"))) + (build-system r-build-system) + (propagated-inputs `(("r-rcpp" ,r-rcpp))) + (home-page "https://github.com/bnosac/BTM") + (synopsis "Biterm Topic Models for Short Text") + (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) +@url{https://github.com/xiaohuiyan/xiaohuiyan.github.io/blob/master/paper/\ +BTM-WWW13.pdf}.") + (license license:asl2.0))) |