{
  "altLabels": [
    "VSM"
  ],
  "definition": "A classical information-retrieval model that represents documents and queries as vectors in a term space and compares them using vector similarity.",
  "distinctions": [
    {
      "reason": "The classical vector space model usually uses sparse term-weighted vectors; dense retrieval uses learned dense representations.",
      "statement": "Vector Space Model is not Dense Retrieval.",
      "target": "dense-retrieval",
      "targetLabel": "Dense Retrieval",
      "targetUri": "https://id.searchplex.net/dense-retrieval/"
    },
    {
      "reason": "The vector space model is a retrieval model over term-weighted vectors; an embedding is a learned vector representation that may be used in many retrieval or non-retrieval settings.",
      "statement": "Vector Space Model is not Embedding.",
      "target": "embedding",
      "targetLabel": "Embedding",
      "targetUri": "https://id.searchplex.net/embedding/"
    },
    {
      "reason": "The vector space model is a classical term-vector retrieval model; vector search is a broad practitioner term often used for retrieval over learned vector embeddings.",
      "statement": "Vector Space Model is not Vector Search.",
      "target": "vector-search",
      "targetLabel": "Vector Search",
      "targetUri": "https://id.searchplex.net/vector-search/"
    }
  ],
  "id": "vector-space-model",
  "kind": "Representation",
  "license": "https://creativecommons.org/publicdomain/zero/1.0/",
  "links": [
    {
      "label": "Scoring, term weighting and the vector space model",
      "type": "canonicalSurvey",
      "url": "https://nlp.stanford.edu/IR-book/html/htmledition/scoring-term-weighting-and-the-vector-space-model-1.html"
    }
  ],
  "modifiedAt": "2026-09-14T06:43:46Z",
  "prefLabel": "Vector Space Model",
  "publisher": {
    "name": "Searchplex",
    "url": "https://searchplex.net/"
  },
  "relations": [
    {
      "note": "The classical vector space model usually uses sparse term-weighted vectors; dense retrieval uses learned dense representations.",
      "target": "dense-retrieval",
      "type": "notEquivalentTo"
    },
    {
      "note": "The vector space model is a retrieval model over term-weighted vectors; an embedding is a learned vector representation that may be used in many retrieval or non-retrieval settings.",
      "target": "embedding",
      "type": "notEquivalentTo"
    },
    {
      "note": "The vector space model is a classical term-vector retrieval model; vector search is a broad practitioner term often used for retrieval over learned vector embeddings.",
      "target": "vector-search",
      "type": "notEquivalentTo"
    },
    {
      "target": "lexical-retrieval",
      "type": "related"
    },
    {
      "target": "sparse-retrieval",
      "type": "related"
    },
    {
      "target": "tf-idf",
      "type": "related"
    },
    {
      "target": "vector-search",
      "type": "related"
    }
  ],
  "representations": {
    "html": "https://id.searchplex.net/vector-space-model/",
    "json": "https://id.searchplex.net/vector-space-model.json",
    "jsonld": "https://id.searchplex.net/vector-space-model.jsonld"
  },
  "scheme": "https://id.searchplex.net/scheme/",
  "scopeNote": "This ID uses Vector Space Model in the classical IR sense: sparse term-weighted query and document vectors, often using TF-IDF-style weights. It should not be read as a generic label for modern embedding search, vector databases, approximate nearest-neighbor search, or dense vector retrieval merely because those systems also operate over vectors.",
  "status": "published",
  "uri": "https://id.searchplex.net/vector-space-model/"
}