Hierarchical quantization for fast inner product search
Topics: Chunk Relevance, Document Classification, Probably in use
The Google patent describes an efficient system and method for rapidly calculating inner products, particularly between high-dimensionality vectors, which is a core problem in Maximum Inner Product Search (MIPS). It achieves this speedup using a technique called hierarchical quantization, which involves clustering data vectors and encoding them using a multi-layered system, often combining Vector Quantization (VQ) and Product Quantization (PQ), to significantly reduce computation time and memory usage while maintaining high accuracy. This quantized representation of database items can then be used to quickly categorize new items or find similar items in a database in response to a query.
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