Liana Patel | ACORN: Performant and Predicate-Agnostic Hybrid Search | #60

Disseminate: The Computer Science Research Podcast

In this episode, we chat with with Liana Patel to discuss ACORN, a groundbreaking method for hybrid search in applications using mixed-modality data. As more systems require simultaneous access to embedded images, text, video, and structured data, traditional search methods struggle to maintain efficiency and flexibility. Liana explains how ACORN, leveraging Hierarchical Navigable Small Worlds (HNSW), enables efficient, predicate-agnostic searches by introducing innovative predicate subgraph traversal. This allows ACORN to outperform existing methods significantly, supporting complex query semantics and achieving 2–1,000 times higher throughput on diverse datasets. Tune in to learn more!

Links:

  • ACORN: Performant and Predicate-Agnostic Search Over Vector Embeddings and Structured Data [SIGMOD'24]
  • Liana's LinkedIn
  • Liana's X

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