A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf
.
WCLOUDVIZ: Word Cloud Visualization of Indonesian News Articles Classification Based on Latent Dirichlet Allocation
2018
TELKOMNIKA (Telecommunication Computing Electronics and Control)
Latent Dirichlet Allocation (LDA) is a widely implemented approach for extracting hidden topics in documents generated by soft clustering of a word based on document co-occurrence as a multinomial probability distribution over terms. Therefore, several visualizations have been developed, such as matrices design, text-based design, tree design, parallel coordinates, and force-directed graphs. Furthermore, based on a set of documents representing a class (category), we can implement
doi:10.12928/telkomnika.v16i4.8194
fatcat:je7qtszy4nfahpt4ii5bzsgc24