How Many Topics? Stability Analysis for Topic Models
[bibtex](@incollection{greene2014many,
title={How many topics? stability analysis for topic models},
author={Greene, Derek and O’Callaghan, Derek and Cunningham, P{'a}draig},
booktitle={Machine Learning and Knowledge Discovery in Databases},
pages={498--513},
year={2014},
publisher={Springer}
})
Idea:
a term-centric stability approach for selecting the number of topics in a corpus, based on the agreement between term rankings generated over multiple runs of the same algorithm. Employed a “top-weighted” ranking measure, where higher-ranked terms have a greater degree of influence when calculating agreement scores.
How Many Topics? Stability Analysis for Topic Models
[bibtex](@incollection{greene2014many, title={How many topics? stability analysis for topic models}, author={Greene, Derek and O’Callaghan, Derek and Cunningham, P{'a}draig}, booktitle={Machine Learning and Knowledge Discovery in Databases}, pages={498--513}, year={2014}, publisher={Springer} })
Idea: