= Brown clustering
{wiki=Brown_clustering}
Brown clustering is a hierarchical clustering algorithm used primarily in natural language processing (NLP) to group words or phrases based on their co-occurrence in a text corpus. Developed by Peter Brown and his colleagues in the early 1990s, the method aims to identify clusters of words that share similar contexts, thereby capturing a form of semantic similarity. \#\#\# Key Concepts: 1. **Co-occurrence**: The method evaluates how often words appear together in the same contexts (e.g.
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