vektoriperusteisen

Vektoriperusteinen is a Finnish adjective meaning vector-based, used to describe methods, representations, or technologies that rely on vector quantities or vector space representations as their core. The form vektoriperusteisen is the genitive singular, used to modify a noun in contexts such as vektoriperusteisen lähestymistavan or vektoriperusteisen mallin.

In practice, vektoriperusteiset approaches are common in information retrieval, natural language processing, computer vision, and data science. They represent data as continuous vectors in high-dimensional spaces and use distances or similarities between vectors—such as cosine similarity or Euclidean distance—to perform tasks like search, clustering, classification, and recommendation. Word embeddings, image feature vectors, and various forms of embeddings (text, audio, graph) are typical examples of the vector representations underlying vektoriperusteiset järjestelmät. This contrasts with keyword-based or rule-based methods that operate on discrete symbols rather than numerical vector representations.

Finnish usage treats vektoriperusteinen as a compound-like descriptor that can attach to nouns in different grammatical cases, so phrases such as vektoriperusteinen malli, vektoriperusteisen menetelmän, or vektoriperusteiseen lähestymistapaan are common depending on sentence structure. The term is widely used across technical literature and media to signify a shift from traditional symbolic approaches to representation-based techniques that leverage continuous vector spaces.