Vector Space Retrieval
Vector Space Retrieval is an information retrieval model that represents documents and queries as vectors in a high-dimensional space, where similarity is determined by the cosine of the angle between vectors, distinguishing it from other retrieval models by its use of geometric relationships to rank document relevance.
365
Publications
37.3K
Citations
924
Authors
372
Institutions
Publications per year
2017–2026
59
Variants
Vector Space ModelVsm
Parents
365
A vector space model for automatic indexing
Gerard Salton, Anita M.-Y. Wong, Chul‐Su Yang · Communications of the ACM · 1975 · 7.4K citations · Full text
Omar Khattab, Matei Zaharia · 2020 · 1.1K citations
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Institut national de recherche en sciences et technologies du numérique, France
5 publications · 942 citations
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372

The University of Melbourne
Melbourne, Australia
8 h-index
17 publications
544 citations
Tsinghua University
Beijing, China
8 h-index
18 publications
2.4K citations

University of Regina
Regina, Canada
7 h-index
15 publications
1.9K citations
Google (United States)
Mountain View, United States
6 h-index
19 publications
3K citations

Cornell University
Ithaca, United States
6 h-index
12 publications
23.4K citations

University of Waterloo
Waterloo, Canada
6 h-index
13 publications
770 citations
Stanford University
Stanford, United States
6 h-index
9 publications
3K citations
Institut national de recherche en sciences et technologies du numérique
Le Chesnay-Rocquencourt, France
6 h-index
12 publications
1.8K citations
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Repository · 12 publications · 667 citations
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9 publications · 500 citations
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Conference · 8 publications · 1.2K citations
8
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8 publications · 499 citations
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JASIS · 8 publications · 467 citations
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