{
  "id": "topic:hybrid-retrieval",
  "_kind": "Topic",
  "_file": "domain/topics/topics-knowledge-patterns.yaml",
  "_cluster": "domain",
  "attributes": {
    "displayName": "Hybrid Retrieval",
    "description": "Hybrid Retrieval as a cross-cutting topic — combining dense vector\nsimilarity with sparse keyword matching for better retrieval quality.\nCovers reciprocal rank fusion (RRF) for merging ranked lists,\nlinear score combination with tunable weights, Weaviate's built-in\nhybrid search, Pinecone's sparse-dense vectors, and the empirical\nfinding that hybrid consistently outperforms either method alone\non diverse query types. The key design decision is the fusion\nstrategy and how to weight semantic vs lexical signals.\n"
  },
  "outgoingEdges": [
    {
      "from": "topic:hybrid-retrieval",
      "to": "domain:software-engineering",
      "kind": "applies_to"
    },
    {
      "from": "topic:hybrid-retrieval",
      "to": "domain:data-science",
      "kind": "applies_to"
    },
    {
      "from": "topic:hybrid-retrieval",
      "to": "specialization:ai-agents-conversational",
      "kind": "applies_to"
    }
  ],
  "incomingEdges": [
    {
      "from": "domain:knowledge-management",
      "to": "topic:hybrid-retrieval",
      "kind": "contains"
    },
    {
      "from": "tool:weaviate",
      "to": "topic:hybrid-retrieval",
      "kind": "relates_to_topic",
      "attributes": {}
    },
    {
      "from": "tool:pinecone",
      "to": "topic:hybrid-retrieval",
      "kind": "relates_to_topic",
      "attributes": {}
    },
    {
      "from": "topic:rag-pipeline-design",
      "to": "topic:hybrid-retrieval",
      "kind": "related_topics"
    }
  ]
}