Knowledge & Data · Software component
Parallel Fusion Retriever
Software componentKnowledge & DataKnowledge & Dataarc:ParallelFusionRetriever
A hybrid retriever that queries the vector index and the knowledge graph independently in parallel and merges their results.
Responsibility. Queries vector and graph sources in parallel and merges results.
Also known as: Parallel querying, Hybrid vector-plus-graph RAG retrieval
Variant of Hybrid Retriever abstract
When to choose. Choose when you cannot predict whether vector search or the graph will surface the needed information, trading complexity for completeness.
Relationships
invokes dependency
- Graph Retriever Ch5.13
- Reranker abstract Ch1.7B
- Vector Retriever abstract Ch5.13
sends data to dynamic
- Context Assembler abstract Ch5.13
alternative to variability
Design guidance
- MUST deduplicate merged results and rank them by combining semantic scores with graph proximity, presenting one coherent result set.
Classification
- Patterns
- Parallel retrieval with result fusion
- Quality attributes
- Functional suitability: correctness and validity (ISO/IEC 25010 | NIST AI RMF: valid)
- Risks mitigated
- Coverage gaps where relationship edges do not yet exist
Sources
- Ch1.7B: T. Nguyen, "Relational Reasoning with Knowledge Graphs - Hybrid RAG+KG Integration," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 1.7B. ISBN: 9798244538229.
- Ch5.13: T. Nguyen, "Hybrid Decision Systems Fundamentals," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 5.13. ISBN: 9798244538229.