Search Results for author:
Found 7 papers, 5 papers with code
Starling: An I/O-Efficient Disk-Resident Graph Index Framework for High-Dimensional Vector Similarity Search on Data Segment
In this paper, we present Starling, an I/O-efficient disk-resident graph index framework that optimizes data layout and search strategy within the segment.
MUST: An Effective and Scalable Framework for Multimodal Search of Target Modality
We investigate the problem of multimodal search of target modality, where the task involves enhancing a query in a specific target modality by integrating information from auxiliary modalities.
Prompting Disentangled Embeddings for Knowledge Graph Completion with Pre-trained Language Model
Accordingly, we propose a new KGC method named PDKGC with two prompts -- a hard task prompt which is to adapt the KGC task to the PLM pre-training task of token prediction, and a disentangled structure prompt which learns disentangled graph representation so as to enable the PLM to combine more relevant structure knowledge with the text information.
Routing-Guided Learned Product Quantization for Graph-Based Approximate Nearest Neighbor Search
It suffers from the large-scale $\mathcal{X}$ because a PG with full vectors is too large to fit into the memory, e. g., a billion-scale $\mathcal{X}$ in 128 dimensions would consume nearly 600 GB memory.
DiskANN++: Efficient Page-based Search over Isomorphic Mapped Graph Index using Query-sensitivity Entry Vertex
The main drawback of graph-based ANNS is that a graph index would be too large to fit into the memory especially for a large-scale $\mathcal{X}$.
Navigable Proximity Graph-Driven Native Hybrid Queries with Structured and Unstructured Constraints
We easily deploy existing various PGs on this framework to process hybrid queries efficiently.
A Comprehensive Survey and Experimental Comparison of Graph-Based Approximate Nearest Neighbor Search
Approximate nearest neighbor search (ANNS) constitutes an important operation in a multitude of applications, including recommendation systems, information retrieval, and pattern recognition.
