2 citations · 2 across the 1 of their papers we have counts for
5 papers
RISK: Efficiently processing rich spatial-keyword queries on encrypted geo-textual data
Zhen Lv, Cong Cao, Hongwei Huo +4
Symmetric searchable encryption (SSE) for geo-textual data has attracted significant attention. However, existing schemes rely on task-specific, incompatible indices for isolated s…
Fast Tuning the Index Construction Parameters of Proximity Graphs in Vector Databases
Wenyang Zhou, Jiadong Xie, Yingfan Liu +6
k-approximate nearest neighbor search (k-ANNS) in high-dimensional vector spaces is a fundamental problem across many fields. With the advent of vector databases and retrieval-augm…
Privacy-Preserving Approximate Nearest Neighbor Search on High-Dimensional Data
Yingfan Liu, Yandi Zhang, Jiadong Xie +3
In the era of cloud computing and AI, data owners outsource ubiquitous vectors to the cloud, which furnish approximate -nearest neighbors (-ANNS) services to users. To protec…
KBest: Efficient Vector Search on Kunpeng CPU
Kaihao Ma, Meiling Wang, Senkevich Oleg +19
Vector search, which returns the vectors most similar to a given query vector from a large vector dataset, underlies many important applications such as search, recommendation, and…
Revisiting the Index Construction of Proximity Graph-Based Approximate Nearest Neighbor Search
Shuo Yang, Jiadong Xie, Yingfan Liu +5
Proximity graphs (PG) have gained increasing popularity as the state-of-the-art solutions to -approximate nearest neighbor (-ANN) search on high-dimensional data, which serve…