After clustering the articles into 11 topics, we find the average embedding of the clusters. We match an embedding to a cluster and predict that the embedding's article chares common words.
Key insights from a Latent Dirichlet Allocation model
Using Celonis analyses to improve the ratings and profitability of a small pizzeria
