most citedHow Much Can Time-related Features Enhance Time Series Forecasting?

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cs.DB2025

All-in-one Graph-based Indexing for Hybrid Search on GPUs

Zhonggen Li, Yougen Li, Yifan Zhu +3

Hybrid search has emerged as a promising paradigm that combines lexical and semantic retrieval, enhancing accuracy for applications such as recommendations, information retrieval,…

cs.DB2025

Scalable Graph Indexing using GPUs for Approximate Nearest Neighbor Search

Zhonggen Li, Xiangyu Ke, Yifan Zhu +3

Approximate nearest neighbor search (ANNS) in high-dimensional vector spaces has a wide range of real-world applications. Numerous methods have been proposed to handle ANNS efficie…

cs.DB2025

Balancing the Blend: An Experimental Analysis of Trade-offs in Hybrid Search

Mengzhao Wang, Boyu Tan, Yunjun Gao +5

Hybrid search, the integration of lexical and semantic retrieval, has become a cornerstone of modern information retrieval systems, driven by demanding applications like Retrieval-…

cs.DB2025

Empowering Graph-based Approximate Nearest Neighbor Search with Adaptive Awareness Capabilities

Jiancheng Ruan, Tingyang Chen, Renchi Yang +2

Approximate Nearest Neighbor Search (ANNS) in high-dimensional spaces finds extensive applications in databases, information retrieval, recommender systems, etc. While graph-based…

cs.DB2025

In-context Clustering-based Entity Resolution with Large Language Models: A Design Space Exploration

Jiajie Fu, Haitong Tang, Arijit Khan +3

Entity Resolution (ER) is a fundamental data quality improvement task that identifies and links records referring to the same real-world entity. Traditional ER approaches often rel…

cs.DB2025

Stitching Inner Product and Euclidean Metrics for Topology-aware Maximum Inner Product Search

Tingyang Chen, Cong Fu, Xiangyu Ke +3

Maximum Inner Product Search (MIPS) is a fundamental challenge in machine learning and information retrieval, particularly in high-dimensional data applications. Existing approache…