Hercules — Against Data Series Similarity Search

SIGKDD 2022 paper introducing BLISS, a billion-scale indexing method using iterative re-partitioning for large-scale approximate nearest neighbor search.

Research paper introducing CAPS, a practical partition index designed for filtered similarity search. Published as an arXiv preprint in 2023 by Gaurav Gupta et al., it addresses the challenge of combining attribute filtering with approximate nearest neighbor search efficiently.

VLDB 2024 paper presenting DIDS, a fast similarity search method using double indices and double summarizations to accelerate high-dimensional vector queries.

TKDE 2024 paper presenting DIMS, a distributed indexing method for efficient similarity search across metric spaces. The approach enables parallel processing of vector similarity queries at scale.

Research paper presenting Maze, a web-scale video deduplication system designed for cost efficiency. Published at the 30th ACM International Conference on Multimedia in 2022, it addresses large-scale video similarity detection.

NeurIPS 2023 paper presenting NHQ, an efficient and robust framework for approximate nearest neighbor search with attribute constraints, enabling hybrid queries combining vector similarity with structured filtering.