Vector space model
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The vector space model (VSM) is an algebraic model used for information filtering and information retrieval. It represents natural language documents in a formal manner by the use of vectors in a multi-dimensional space. It was used for the first time by the SMART Information Retrieval System.
Models based on and extending the vector space model include:
- Generalized vector space model
- Topic-based vector space model (TVSM) — Extends the vector space model by removing the constraint that the term-vectors be orthogonal. In contrast to the generalized vector space model the topic-based vector space model does not depend on concurrence-based similarities between terms.
- Latent semantic analysis
- DSIR model
Further reading
- G. Salton, A. Wong, and C. S. Yang (1975), "[A Vector Space Model for Automatic Indexing]," Communications of the ACM, vol. 18, nr. 11, pages 613–620. (The article in which the vector space model was first presented)
- [Description of the vector space model]
- [Description of the topic-based vector space model]
See also
Inverted index
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