From 6e671c7691eb3752f1d1a20f719b7b319dba3979 Mon Sep 17 00:00:00 2001 From: silviatti Date: Wed, 18 Dec 2019 10:36:50 +0100 Subject: [PATCH] Update README.md --- README.md | 10 +++++++--- 1 file changed, 7 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index 75c4fc5..d91dfe7 100644 --- a/README.md +++ b/README.md @@ -1,7 +1,7 @@ #

Constrained Relational Topic Models

+Implementation of Constrained Relational Topic Models (C-RTM), proposed in the paper "Constrained Relational Topic Models" [https://doi.org/10.1016/j.ins.2019.09.039] accepted in Information Sciences, 2020. +CRTM is a family of topic models that extend the well-know Relational Topic Models (Chang, 2009). It models the structure of a document network and incorporates other types of relational information obtained by prior domain knowledge. This implementation extends the code from the package of ([Weiwei Yang](http://cs.umd.edu/~wwyang/)'s). -This is an extension of Relational Topic Models, called Constrained Relational Topic Models (C-RTM). It extends the code from the package of ([Weiwei Yang](http://cs.umd.edu/~wwyang/)'s). -C-RTM models the structure of a document network and incorporates other types of relational information obtained by prior domain knowledge. ##

Execution of the program in Command Line

``` @@ -49,9 +49,13 @@ java -cp YWWTools.jar:deps.jar yang.weiwei.Tools --tool lda --model lda --constr Three benchmark relational [datasets](http://www.cs.umd.edu/~sen/lbc-proj/LBC.html) are included in their related folders. They are already preprocessed and ready to be used as input for the model. Notice that the file `labels.txt` can be used to create the must- and cannot-constraints. Two random documents can be extracted and if their labels are the same, a must-constraint may be added to the ``, otherwise a cannot-constraint may be added. - +

[References](#references) ###

[SC-LDA](#sclda): Sparse Constrained LDA Yang, Y., Downey, D., Boyd-Graber, J.: Efficient Methods for Incorporating Knowledge into Topic Models. In: Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing (EMNLP). pp. 308-317 (2015) +###

[RTM](#rtm): Relational Topic Models + +Jonathan Chang, David M. Blei: Relational Topic Models for Document Networks. In: Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics (AISTATS) 2009: 81-88 + [Back to Top](#top)