Foundations of Vector Retrieval

Author:   Sebastian Bruch
Publisher:   Springer International Publishing AG
Edition:   1st ed. 2024
ISBN:  

9783031551819


Pages:   185
Publication Date:   28 March 2024
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Foundations of Vector Retrieval


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Overview

This book presents the fundamentals of vector retrieval. To this end, it delves into important data structures and algorithms that have been successfully used to solve the vector retrieval problem efficiently and effectively. This monograph is divided into four parts. The first part introduces the problem of vector retrieval and formalizes the concepts involved. The second part delves into retrieval algorithms that help solve the vector retrieval problem efficiently and effectively. It includes a chapter each on brand-and-bound algorithms, locality sensitive hashing, graph algorithms, clustering, and sampling. Part three is devoted to vector compression and comprises chapters on quantization and sketching. Finally, the fourth part presents a review of background material in a series of appendices, summarizing relevant concepts from probability, concentration inequalities, and linear algebra. The book emphasizes the theoretical aspects of algorithms and presents related theorems and proofs. It is thus mainly written for researchers and graduate students in theoretical computer science and database and information systems who want to learn about the theoretical foundations of vector retrieval.

Full Product Details

Author:   Sebastian Bruch
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Edition:   1st ed. 2024
ISBN:  

9783031551819


ISBN 10:   3031551818
Pages:   185
Publication Date:   28 March 2024
Audience:   College/higher education ,  Postgraduate, Research & Scholarly
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

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Sebastian Bruch works at Pinecone in the United States as a research scientist. His research is centered around probabilistic data structures and approximate algorithms for retrieval, and efficient inference algorithms for learnt ranking functions. He is presently serving as an Associate Editor with the ACM TOIS journal.

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