Understanding the Performance of Hierarchical Navigable Small World (HNSW) in the Facebook FAISS Library for Indexing Large Databases – Bilal RAZA
Bilal RAZA
Master's thesis
Understanding the Performance of Hierarchical Navigable Small World (HNSW) in the Facebook FAISS Library for Indexing Large Databases
Abstract:
This thesis explores the performance of the Hierarchical Navigable Small Worlds (HNSW) algorithm within the FAISS library for indexing large databases. As data volumes grow exponentially, Approximate Nearest Neighbor (ANN) algorithms, like HNSW, offer efficient solutions. HNSW constructs a hierarchical graph structure, demonstrating superiority over other ANN algorithms. However, its performance within …moreAbstract:
This thesis explores the performance of the Hierarchical Navigable Small Worlds (HNSW) algorithm within the FAISS library for indexing large databases. As data volumes grow exponentially, Approximate Nearest Neighbor (ANN) algorithms, like HNSW, offer efficient solutions. HNSW constructs a hierarchical graph structure, demonstrating superiority over other ANN algorithms. However, its performance within …more
Language used: English
Date on which the thesis was submitted / produced: 9. 2. 2024
Thesis defence
- Supervisor: prof. Dr. Andreas Fischer
Citation record
ISO 690-compliant citation record:
RAZA, Bilal. \textit{Understanding the Performance of Hierarchical Navigable Small World (HNSW) in the Facebook FAISS Library for Indexing Large Databases}. Online. Master's thesis. České Budějovice: University of South Bohemia in České Budějovice, Faculty of Science. 2024. Available from: https://theses.cz/id/7bj92a/.
The right form of listing the thesis as a source quoted
RAZA, Bilal. Understanding the Performance of Hierarchical Navigable Small World (HNSW) in the Facebook FAISS Library for Indexing Large Databases. České Budějovice, 2024. diplomová práce (Mgr.). JIHOČESKÁ UNIVERZITA V ČESKÝCH BUDĚJOVICÍCH. Přírodovědecká fakulta
Full text of thesis
Contents of on-line thesis archive
Published in Theses:- Soubory jsou nedostupné do 9. 2. 2027
- Po tomto datu bude práce dostupná: světu
Other ways of accessing the text
Institution archiving the thesis and making it accessible: JIHOČESKÁ UNIVERZITA V ČESKÝCH BUDĚJOVICÍCH, Přírodovědecká fakultaUNIVERSITY OF SOUTH BOHEMIA IN ČESKÉ BUDĚJOVICE
Faculty of ScienceMaster programme / field:
Artificial Intelligence and Data Science / Artificial Intelligence and Data Science
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