• co-occurrence analysis
• Finding possibly related entities
• visualizing high-dimensional data (PCA)
• Manifold learning (Isomap, t-SNE)
• Clustering (k-means, GMMs, CH index)
• clustering (DP-GMMs, DP-means), topic modeling (LDA)
• model evaluation (including confusion matrices, ROC curves)