Titlebook: Database Systems for Advanced Applications; 26th International C Christian S. Jensen,Ee-Peng Lim,Chih-Ya Shen Conference proceedings 2021 T

不可比擬

漂泊

Partial Solutions for Patient Safetyletion methods are known to be primarily knowledge embedding based models, which are broadly classified as translational models and neural network models. However, both kinds of models are single-task based models and hence fail to capture the underlying inter-structural relationships that are inher

phytochemicals

Multi-job Merging Framework and Scheduling Optimization for Apache Flinkighlighted as follows: (1) the framework enables Flink to support multi-job collection, merging and dynamic tuning of the execution sequence, and the selection of these functions are customizable. (2) with the multi-job merging and optimization, the total running time can be reduced by 31% compared

stress-response

花費(fèi)

vRaft: Accelerating the Distributed Consensus Under Virtualized Environments followers to accelerate both the write and the read requests processing in a virtualized cloud environment, without affecting the linearizability guarantee of Raft. The experiments based on the virtual nodes in Tencent Cloud indicate that vRaft improves the throughput by up?to 64.2%, reduces averag

Inscrutable

背信

Label Contrastive Coding Based Graph Neural Network for Graph Classificationc label memory bank and a momentum updated encoder. Our extensive evaluations with eight benchmark graph datasets demonstrate that LCGNN can outperform state-of-the-art graph classification models. Experimental results also verify that LCGNN can achieve competitive performance with less training dat

共棲

Keyword-Centric Community Search over Large Heterogeneous Information Networks design an advanced algorithm .-core using a new method of traversing the search space based on trees to accelerate the searching procedure. For online queries, we optimize the approach with a new index to handle the online queries of community search over HINs. Extensive experiments on HINs are con

和平主義

KGSynNet: A Novel Entity Synonyms Discovery Framework with Knowledge Graphedge information into their semantic features. We conduct extensive experiments to demonstrate the effectiveness of our . in leveraging the knowledge graph. The experimental results show that the . improves the state-of-the-art methods by 14.7% in terms of hits@3 in the offline evaluation and outper

虛假