About This Document
- sl:arxiv_author : Sebastian Bruch
- sl:arxiv_firstAuthor : Sebastian Bruch
- sl:arxiv_num : 2401.09350
- sl:arxiv_published : 2024-01-17T17:13:35Z
- sl:arxiv_summary : Vectors are universal mathematical objects that can represent text, images,
speech, or a mix of these data modalities. That happens regardless of whether
data is represented by hand-crafted features or learnt embeddings. Collect a
large enough quantity of such vectors and the question of retrieval becomes
urgently relevant: Finding vectors that are more similar to a query vector.
This monograph is concerned with the question above and covers fundamental
concepts along with advanced data structures and algorithms for vector
retrieval. In doing so, it recaps this fascinating topic and lowers barriers of
entry into this rich area of research.@en
- sl:arxiv_title : Foundations of Vector Retrieval@en
- sl:arxiv_updated : 2024-01-17T17:13:35Z
- sl:bookmarkOf : https://arxiv.org/abs/2401.09350
- sl:creationDate : 2024-01-18
- sl:creationTime : 2024-01-18T14:57:59Z
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