Collection needs to have a DOI as an ID.


@id00747eb3-825b-4e51-8f66-bc0f996edc42
name?GTM
@typeDataset?
description?This demo is the sampling inference for Graph Topic Model, and more details about this model can be found in the following reference: @ARTICLE{7015568, author={J. Xuan and J. Lu and G. Zhang and X. Luo}, journal={IEEE Transactions on Cybernetics}, title={Topic Model for Graph Mining}, year={2015}, volume={45}, A Markov chain Monte Carlo (MCMC) algorithm is developed and implemented to inference the Graph Topic Model (GTM). GTM is a probabilistic graphical model for the data represented by graph structure, e.g., chemical formulas or documents.
isPartOfGTM
datePublished?2018-03-10
creator?
  • J. Xuan
  • J. Lu
  • G. Zhang
  • X. Luo
path?GTM
contact?J. Xuan
citation?Topic Model for Graph Mining
hasPart?
identifier?GTM
license?GPL 3
publisher?University of Technology Sydney

This file was created at 2018-09-25T06:15:13.152Z by Calcyte which implements the Draft DataCrate Packaging format, version 0.3