Titlebook: Database Systems for Advanced Applications; 27th International C Arnab Bhattacharya,Janice Lee Mong Li,Rage Uday Ki Conference proceedings

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Efficient In-Memory Evaluation of Reachability Graph Pattern Queries on Data Graphsnalysis of large data graphs. In this paper, we present a novel approach for efficiently finding homomorphic matches of graph pattern queries, where pattern edges denote reachability relationships between nodes in the data graph. We first propose the concept of query reachability graph to compactly

NEG

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-join: Efficient Join with Versioned Dimension Tablesces and contexts that are referenced from the fact tables. Analytical business queries join both tables to provide and verify business findings. Business resources and contexts are not necessarily constant; the dimension table may be updated at times. Versioning preserves every version of a dimensio

Type-1-Diabetes

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Triple-as-Node Knowledge Graph and Its Embeddingsct triples (.). However, most previous KGs only consider the relationship between individual entities, ignoring connections between facts and entities, which are commonly used to depict useful information about the properties of facts. To this end, we formally introduce ., a new KG form which incorp

indignant

刚开始

TRHyTE: Temporal Knowledge Graph Embedding Based on Temporal-Relational Hyperplanesyperplane-based TKGE approach, namely HyTE, has achieved remarkable performance, it still suffers from several problems including (i) ignorance of latent temporal properties and diversity of relations; (ii) neglect of temporal dependency between adjacent hyperplanes; (iii) inefficient static random

mechanism

ExKGR: Explainable Multi-hop Reasoning for Evolving Knowledge Graphdding-based approach, multi-hop reasoning approach is more interpretable. Multi-hop reasoning can be modeled as . (RL) in which the RL agent navigates in the KG. Despite high interpretability, the knowledge in real world evolves by the minute, previous approaches are based on static KG. To address t

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Counterfactual-Guided and Curiosity-Driven Multi-hop Reasoning over Knowledge Grapheffectiveness and interpretability. It typically adopts the Reinforcement Learning (RL) framework and traverses over the KG to reach the target answer and find evidential paths. However, existing methods often give all reached paths equal hit rewards. Intuitively, not all paths have the same contrib