104 citations · 118 across the 8 of their papers we have counts for
9 papers
MatrixGate: A High-performance Data Ingestion Tool for Time-series Databases
Shuhui Wang, Zihan Sun, Chaochen Hu +5
Recent years have seen massive time-series data generated in many areas. This different scenario brings new challenges, particularly in terms of data ingestion, where existing tech…
GPU-Accelerated OLTP: An In-Depth Analysis of Concurrency Control Schemes
Zihan Sun, Yuyu Luo, Yong Zhang +2
Over the past decade, GPUs have demonstrated significant potential in accelerating Online Analytical Processing (OLAP) operations. However, there remains a substantial gap in their…
E4SRec: An Elegant Effective Efficient Extensible Solution of Large Language Models for Sequential Recommendation
Xinhang Li, Chong Chen, Xiangyu Zhao +2
The recent advancements in Large Language Models (LLMs) have sparked interest in harnessing their potential within recommender systems. Since LLMs are designed for natural language…
OpenSiteRec: An Open Dataset for Site Recommendation
Xinhang Li, Xiangyu Zhao, Yejing Wang +5
As a representative information retrieval task, site recommendation, which aims at predicting the optimal sites for a brand or an institution to open new branches in an automatic d…
IMF: Interactive Multimodal Fusion Model for Link Prediction
Xinhang Li, Xiangyu Zhao, Jiaxing Xu +2
Link prediction aims to identify potential missing triples in knowledge graphs. To get better results, some recent studies have introduced multimodal information to link prediction…
Jointly Learning Knowledge Embedding and Neighborhood Consensus with Relational Knowledge Distillation for Entity Alignment
Xinhang Li, Yong Zhang, Chunxiao Xing
Entity alignment aims at integrating heterogeneous knowledge from different knowledge graphs. Recent studies employ embedding-based methods by first learning the representation of…
Updatable Learned Index with Precise Positions
Jiacheng Wu, Yong Zhang, Shimin Chen +3
Index plays an essential role in modern database engines to accelerate the query processing. The new paradigm of "learned index" has significantly changed the way of designing inde…
Trimming the Sail: A Second-order Learning Paradigm for Stock Prediction
Chi Chen, Li Zhao, Wei Cao +2
Nowadays, machine learning methods have been widely used in stock prediction. Traditional approaches assume an identical data distribution, under which a learned model on the train…
Improving Distributed Similarity Join in Metric Space with Error-bounded Sampling
Jiacheng Wu, Yong Zhang, Jin Wang +3
Given two sets of objects, metric similarity join finds all similar pairs of objects according to a particular distance function in metric space. There is an increasing demand to p…