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Tracking and analyzing the sequence and timing of queries to optimize relationship paths.
Distinct from Query Generation Patterns: Analyzes query behavioral sequences to strengthen graph paths, not for static performance or geographic intent
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ruvector is a Rust-based vector store and graph database designed for local inference and nearest neighbor searches. It utilizes a vector graph database architecture and a graph neural network index to refine search rankings through structural attention. The system includes a hardware-accelerated quantum circuit simulator for executing state-vector simulations and complex search patterns, alongside a WebAssembly inference engine for running vector search and model execution directly in web browsers. The project employs a cognitive container format that bundles models, data, and a bootable mic
Tracks query sequences and timing to strengthen relationship paths between related vectors.