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HVS (Hierarchical Graph Structure)

HVS is a graph-based index structure leveraging Voronoi diagrams for approximate nearest neighbor search in high-dimensional vector spaces. It is directly relevant to vector databases as it provides efficient similarity search capabilities for large-scale vector data.

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About this tool

HVS (Hierarchical Graph Structure)

Source: GitHub Repository

Category: Open Source

Tags: open-source, ann, graph-database, similarity-search


Description

HVS is a graph-based index structure that leverages Voronoi diagrams for approximate nearest neighbor (ANN) search in high-dimensional vector spaces. It is designed to provide efficient similarity search capabilities, making it suitable for large-scale vector data, such as those found in vector databases.


Features

  • Hierarchical Graph Structure: Organizes data points in a multi-level graph for efficient traversals.
  • Voronoi Diagram-Based Partitioning: Utilizes Voronoi diagrams to partition the data space, improving search efficiency.
  • Approximate Nearest Neighbor Search: Enables fast and effective ANN queries in high-dimensional spaces.
  • Large-Scale Data Support: Designed to handle large datasets, common in vector database applications.
  • Command-Line Tools: Provides commands for building the HVS index and performing searches.
  • Example Usage: Offers running examples (e.g., on ImageNet) to demonstrate functionality.
  • Open Source: Available as open-source software for community use and contribution.

Pricing

HVS is open source and free to use.


Links

  • GitHub Repository
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Information

Websitegithub.com
PublishedJun 7, 2025

Categories

1 Item
Open Sources

Tags

4 Items
#open-source
#ANN
#graph database
#similarity search

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