EASC: An exception-aware semantic compression framework for real-world knowledge graphs-Reference-Cited by-同舟云学术

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EASC: An exception-aware semantic compression framework for real-world knowledge graphs

Published:2023-10 Issue: Volume:278 Page:110900
ISSN:0950-7051
Container-title:Knowledge-Based Systems
language:en
Short-container-title:Knowledge-Based Systems

Author:

Jiang Sihang,Feng Jianchuan,Wang Chao,Liu Jingping,Xiong Zhuozhi,Sha Chaofeng,Zheng Weiguo,Liang Jiaqing,Xiao Yanghua

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Management Information Systems,Software

Reference65 articles.

1. Short text entity linking with fine-grained topics;Chen,2018

2. UBAR: User Behavior-Aware Recommendation with knowledge graph;Wu;Knowl.-Based Syst.,2022

3. Reinforcement recommendation reasoning through knowledge graphs for explanation path quality;Balloccu;Knowl.-Based Syst.,2023

4. SParseQA: Sequential word reordering and parsing for answering complex natural language questions over knowledge graphs;Bakhshi;Knowl.-Based Syst.,2022

5. Causality-aware enhanced model for multi-hop question answering over knowledge graphs;Sui;Knowl.-Based Syst.,2022

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Estimation-based optimizations for the semantic compression of RDF knowledge bases;Information Processing & Management;2024-09

2. Efficient Data Structures for Fast and Low-Cost First-Order Logic Rule Mining;2024

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