{
  "altLabels": [
    "Graded Relevance Metric",
    "Graded Metric"
  ],
  "definition": "A family of evaluation metrics designed to use multi-level relevance judgments rather than only binary relevant/not-relevant labels.",
  "derivedRelations": [
    {
      "target": "ndcg",
      "type": "narrower"
    }
  ],
  "id": "graded-relevance-metric",
  "kind": "Metric",
  "license": "https://creativecommons.org/publicdomain/zero/1.0/",
  "links": [
    {
      "label": "Cumulated gain-based evaluation paper",
      "type": "definingReference",
      "url": "https://doi.org/10.1145/582415.582418"
    }
  ],
  "modifiedAt": "2026-09-14T06:43:46Z",
  "prefLabel": "Graded-Relevance Metric",
  "publisher": {
    "name": "Searchplex",
    "url": "https://searchplex.net/"
  },
  "relations": [
    {
      "target": "qrels",
      "type": "related"
    },
    {
      "target": "rank-sensitive-metric",
      "type": "related"
    },
    {
      "target": "relevance-judgment",
      "type": "related"
    }
  ],
  "representations": {
    "html": "https://id.searchplex.net/graded-relevance-metric/",
    "json": "https://id.searchplex.net/graded-relevance-metric.json",
    "jsonld": "https://id.searchplex.net/graded-relevance-metric.jsonld"
  },
  "scheme": "https://id.searchplex.net/scheme/",
  "scopeNote": "Graded-relevance metrics are useful when some results are more relevant than others. nDCG is the common example in IR evaluation.",
  "status": "published",
  "uri": "https://id.searchplex.net/graded-relevance-metric/"
}