TLDR Tech / Data
Clustering Unstructured Text with LLM Embeddings and HDBSCAN
Clustering unstructured text helps automatically discover topics in unlabeled text documents by combining sentence-transformers embeddings with UMAP for dimensionality reduction and HDBSCAN for density-based clustering. This modern pipeline captures semantic meaning far better than traditional methods, automatically determines the number of clusters, and handles noise/outliers gracefully.
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