peopleanalyst

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Semantic candidate↔role ranking via transformer embeddings (US11403597B2 design-around)

Rank a candidate pool against a role by cosine similarity of TRANSFORMER CONTEXTUAL EMBEDDINGS (dense sentence/text embeddings of role + candidate skill/experience text). IP-clean design-around of in-force US11403597B2 — the representation is a dense contextual embedding, explicitly NOT the patent's topic-model (LDA bag-of-words) document vector, and the rank is cosine, NOT token-set overlap. The dense-embedding complement to the PAT-204 token-overlap two-sided matcher (not a fork). Embedding-provider-agnostic: precomputed embeddings OR a pluggable Embedder port with a deterministic mock fallback.

Cluster
Platform
Type
algo
Status
Building
Used by
people-analytics-toolbox, performix

Maturity evidence

Functioning
core/semantic-ranking.ts (cosine over contextual embeddings, deterministic mock embedder + pluggable port) + REST + MCP (job-family-agent.semantic-rank) wired from one contract; 7 passing tests (npm run test:semantic-rank), changed-files typecheck clean, check:spokes + check:standards green.
Valuable
IP-clean ranking routed from the patent-radar sweep; complements the PAT-204 token-overlap matcher with semantic recall. No live consumer yet, and IN-FORCE patent — pending legal review on the non-infringement path before any commercial use.
Understood
docs/PATENT-RADAR-US11403597B2-TRIAGE.md (claim vs design-around table, synthesis decision, provider seam) + spoke README section with mermaid.
Integrated
REST + MCP from one declaration on branch feat/semantic-candidate-ranking-us11403597b2 (PR open, NOT merged); reuses the two-sided ProfileSide vocabulary. No live consumer wiring yet.

How to use it

REST
/api/spokes/job-family-agent/semantic-rank
MCP
job-family-agent.semantic-rank
Data
src/spokes/job-family-agent/core/semantic-ranking.ts

Other Platform capabilities

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Capability detail sourced from the People Analytics Toolbox capability feed (source of truth), snapshot retrieved 2026-07-23.