research(nightly): typed-edge-hnsw — hybrid vector+semantic retrieval in one pass#626
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Nightly RuVector research: Typed-Edge Navigable Graph — integrating knowledge-graph edge types (SameDocument, References, CoOccurs, Temporal, Causal) into NSW navigation for single-pass hybrid vector+semantic retrieval. Three measured variants on 5,000×128-dim synthetic corpus: - VectorOnly: recall@10=0.733, 232μs mean, 4,295 QPS - EdgeExpand(f=0.30): recall@10=0.895, 446μs mean, 2,240 QPS (+22% semantic) - EdgeConstrained: recall@10=0.992, 792μs mean, 1,262 QPS (SameDocument) All acceptance tests pass (cargo run --release -p ruvector-tegraph --bin benchmark). Co-Authored-By: claude-flow <ruv@ruv.net> Claude-Session: https://claude.ai/code/session_01DmGfJmpxVAQ421ygT3phHf
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Summary
Nightly RuVector research (2026-06-30): Typed-Edge Navigable Graph (TENG) — integrates typed knowledge-graph edges (SameDocument, References, CoOccurs, Temporal, Causal) directly into the NSW navigation beam, enabling single-pass hybrid vector+semantic retrieval with no second graph-traversal step.
rand/rand_distrWhat's Included
crates/ruvector-tegraph/— new standalone cratesrc/types.rs:EdgeType,TypedEdge,Nodesrc/graph.rs:NswGraphwith properBinaryHeapbeam searchsrc/variants.rs:TengIndexwith three search variantssrc/dataset.rs: deterministic seeded corpus generationsrc/bin/benchmark.rs: benchmark binary with acceptance testsdocs/adr/ADR-272-typed-edge-hnsw.mddocs/research/nightly/2026-06-30-typed-edge-hnsw/README.mddocs/research/nightly/2026-06-30-typed-edge-hnsw/gist.mdReal Benchmark Numbers
From
cargo run --release -p ruvector-tegraph --bin benchmarkon x86_64 Linux:Dataset: 5,000 nodes × 128 dims, 100 docs × 50 nodes/doc, 500 queries, k=10.
Why This Is Novel
Current graph-RAG systems (GraphRAG, HippoRAG, LightRAG, G-Retriever) all run ANN retrieval and graph traversal as two separate passes. TENG folds typed graph edges into the navigation beam itself — the first RuVector-native approach to single-pass hybrid retrieval. The EdgeExpand variant discovers nodes that are vector-distant but graph-adjacent (22% more semantic coverage) without a second query.
Ecosystem Fit
Connects: RuVector vector search · graph storage · agent memory (ADR-268) · proof-gate (ADR-227) · MCP tools · WASM/edge · ruFlo automation · RVF cognitive packages · Cognitum Seed
Test Plan
cargo build --release -p ruvector-tegraph— clean buildcargo test -p ruvector-tegraph— 4 unit tests passcargo run --release -p ruvector-tegraph --bin benchmark— all 5 acceptance checks passResearch doc
docs/research/nightly/2026-06-30-typed-edge-hnsw/README.mdADR
docs/adr/ADR-272-typed-edge-hnsw.mdGenerated by Claude Code