Similarity

• Vector Space Model

  The vector space model (VSM) represents documents and queries as vectors in a high-dimensional term space and ranks documents by their cosine similarity to the query vector.

• More Like This

  Finds documents similar to a given document using term statistics and relevance scoring. Basis for recommendation and related-document features.

• Dot Product Similarity

  Inner product of two vectors; equivalent to cosine similarity when vectors are unit-normalised; fast to compute in dense retrieval.

• Shingling

  Shingling represents a document as its set of overlapping n-grams (shingles), enabling near-duplicate detection via Jaccard similarity or MinHash approximations.

• Shingle

  A shingle is an n-gram treated as a set element for document comparison. The term signals a shift from positional sequence analysis to set-based similarity measurement.

• Character N-Gram

  A character n-gram is a contiguous sequence of n characters extracted from a string, enabling tokenisation-free indexing, fuzzy search, language identification, and subword modelling.

• Trigram

  A trigram is an n-gram of length 3 — three consecutive tokens considered as a unit. Trigrams extend bigrams with one extra token of context, improving disambiguation at the cost of sparser counts.

• N-Gram

  An n-gram is a contiguous sequence of n tokens drawn from a text, used to capture local word order for indexing, language modelling, and similarity.