{
  "unversionedId": "models/vsknn",
  "id": "models/vsknn",
  "title": "VSKNN",
  "description": "VSKNN stands for Vector Multiplication Session-Based kNN. The idea of this variant is to put more emphasis on the more recent events of a session when computing the similarities. Instead of encoding a session as a binary vector, we use real-valued vectors to encode the current session. Only the very last element of the session obtains a value of “1”; the weights of the other elements are determined using a linear decay function that depends on the position of the element within the session, where elements appearing earlier in the session obtain a lower weight. As a result, when using the dot product as a similarity function between the current weight-encoded session and a binary-encoded past session, more emphasis is given to elements that appear later in the sessions.",
  "source": "@site/docs/models/vsknn.md",
  "sourceDirName": "models",
  "slug": "/models/vsknn",
  "permalink": "/recohut/docs/models/vsknn",
  "editUrl": "https://github.com/sparsh-ai/recohut/docs/models/vsknn.md",
  "tags": [],
  "version": "current",
  "frontMatter": {},
  "sidebar": "tutorialSidebar",
  "previous": {
    "title": "VNCF",
    "permalink": "/recohut/docs/models/vncf"
  },
  "next": {
    "title": "Wide and Deep",
    "permalink": "/recohut/docs/models/wide-and-deep"
  }
}