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

Fibroid

Spatial-Temporal Attention Network for Temporal Knowledge Graph Completiontructural information from the egocentric network of each entity. Additionally, an .aptive .emporal .tention Mechanism (ADTAT) is utilized to flexibly model the correlation of entity representations in the time dimension. Finally, by combing our obtained representations with existing static KG compl

CHIDE

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A Novel Embedding Model for Knowledge Graph Completion Based on Multi-Task Learningn the global representation of each triple element. Such global representations are then integrated into task-specific translational embedding models of each knowledge graph to preserve its transition property. We conduct an extensive empirical evaluation of multi-version . based on different transl

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https://doi.org/10.1007/978-1-4471-4640-7the third-party verifier can audit the integrity of ciphertext without downloading the whole encrypted data. Security analysis shows that our proposed scheme is provably secure under the random oracle model. An evaluation of performance shows that our proposed scheme is efficient in terms of computa

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Consumer Engineering, 1920s–1970s 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

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https://doi.org/10.1007/978-3-030-14564-4edge 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