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This article explains the fundamentals of word vectors in NLP, walks through constructing them via co‑occurrence matrices and dimensionality reduction, demonstrates the process with a concrete example and Python code, and evaluates the resulting embeddings using cosine similarity.
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At Baidu Search, a large‑scale short‑text clustering system was built using multi‑level semantic splitting, fine‑grained aggregation and error‑correction, evolving from v1.0 to v2.0, and now clusters 100 million queries with 95 % accuracy and 80 % recall within three days.
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