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KNOWLEDGE: 作品数：1997被引量：2061H指数：16; 导出分析报告; 相关领域：医药卫生更多>>; 相关作者：徐升华郑菲谢华玲贺西安许培扬更多>>; 相关机构：华中师范大学武汉大学北京航空航天大学北京师范大学更多>>; 相关期刊：更多>>; 相关基金：国家自然科学基金国家社会科学基金国家重点基础研究发展计划国家高技术研究发展计划更多>>

Cyclical Training Framework with Graph Feature Optimization for Knowledge Graph Reasoning: 《Computers, Materials & Continua》2025年第5期1951-1971,共21页Xiaotong Han Yunqi Jiang Haitao Wang Yuan Tian; supported by the National Key Research and Development Program of China(No.2023YFF0905400);the National Natural Science Foundation of China(No.U2341229).; Knowledge graphs(KGs),which organize real-world knowledge in triples,often suffer from issues of incompleteness.To address this,multi-hop knowledge graph reasoning(KGR)methods have been proposed for interpretable know...; 关键词：Knowledge graph reinforcement learning TRANSFORMER

An Improved Knowledge Distillation Algorithm and Its Application to Object Detection: 《Computers, Materials & Continua》2025年第5期2189-2205,共17页Min Yao Guofeng Liu Yaozu Zhang Guangjie Hu; funded by National Natural Science Foundation of China(61603245).; Knowledge distillation(KD)is an emerging model compression technique for learning compact object detector models.Previous KD often focused solely on distilling from the logits layer or the feature intermediate layers,...; 关键词：Deep learning model compression knowledge distillation object detection

Multimodal Neural Machine Translation Based on Knowledge Distillation and Anti-Noise Interaction: 《Computers, Materials & Continua》2025年第5期2305-2322,共18页Erlin Tian Zengchao Zhu Fangmei Liu Zuhe Li; supported by the Henan Provincial Science and Technology Research Project:232102211017,232102211006,232102210044,242102211020 and 242102211007;the ZhengzhouUniversity of Light Industry Science and Technology Innovation Team Program Project:23XNKJTD0205.; Within the realm of multimodal neural machine translation(MNMT),addressing the challenge of seamlessly integrating textual data with corresponding image data to enhance translation accuracy has become a pressing issue...; 关键词：Knowledge distillation anti-noise interaction mask occlusion door control fusion

MMCSD:Multi-Modal Knowledge Graph Completion Based on Super-Resolution and Detailed Description Generation: 《Computers, Materials & Continua》2025年第4期761-783,共23页Huansha Wang Ruiyang Huang Qinrang Liu Shaomei Li Jianpeng Zhang; funded by Research Project,grant number BHQ090003000X03。; Multi-modal knowledge graph completion(MMKGC)aims to complete missing entities or relations in multi-modal knowledge graphs,thereby discovering more previously unknown triples.Due to the continuous growth of data and ...; 关键词：Multi-modal knowledge graph knowledge graph completion multi-modal fusion

Impact of family history of breast disease on knowledge,attitudes,and breast cancer preventive practices among reproductive-age females: 《World Journal of Clinical Oncology》2025年第4期109-118,共10页Melaku Mekonnen Agidew Niguss Cherie Zemene Damtie Bezawit Adane Girma Derso; BACKGROUND Breast cancer is one of the most prevalent causes of morbidity and mortality worldwide,presenting an increasing public health challenge,particularly in lowincome and middle-income countries.However,data on ...; 关键词：Breast cancer Reproductive age KNOWLEDGE ATTITUDE Practice Ethiopia

Attention-Enhanced and Knowledge-Fused Dual Item Representations Network for Recommendation: 《Tsinghua Science and Technology》2025年第2期585-599,共15页Qiang Hua Jiachao Zhou Feng Zhang Chunru Dong Dachuan Xu; supported by the Beijing Natural Science Foundation(No.Z200002);the Innovation Capacity Enhancement Program-Science and Technology Platform Project,Hebei Province(No.22567623H);the Chern Institute of Mathematics,Nankai University.; Integrating Knowledge Graphs(KGs)into recommendation systems as supplementary information has become a prevalent strategy.By leveraging the semantic relationships between entities in KGs,recommendation systems can bet...; 关键词：Recommender System(RS) Knowledge Graph(KG) Graph Neural Networks(GNN) attention mechanism

Syntax-Enhanced Entity Relation Extraction with Complex Knowledge: 《Computers, Materials & Continua》2025年第4期861-876,共16页Mingwen Bi Hefei Chen Zhenghong Yang; funded by the National Key Technology R&D Program of China under Grant No.2021YFD2100605;the National Natural Science Foundation of China under Grant No.62433002;the Project of Construction and Support for High-Level Innovative Teams of Beijing Municipal Institutions under Grant No.BPHR20220104;Beijing Scholars Program under Grant No.099.; Entity relation extraction,a fundamental and essential task in natural language processing(NLP),has garnered significant attention over an extended period.,aiming to extract the core of semantic knowledge from unstruc...; 关键词：Entity relation extraction complex knowledge syntax-enhanced semantic interaction pre-trained BERT

Joint Extraction of Uygur Medicine Knowledge with Edge Computing: 《Tsinghua Science and Technology》2025年第2期782-795,共14页Fan Lu Quan Qi Huaibin Qin; Edge computing,a novel paradigm for performing computations at the network edge,holds significant relevance in the healthcare domain for extracting medical knowledge from traditional Uygur medical texts.Medical knowle...; 关键词：BERT pre-training joint extraction edge computing

PerFedKG:two-stage information-loop federated knowledge graph for personalized privacy-preserving recommendation systems: 《Science China(Information Sciences)》2025年第4期94-95,共2页Fan WANG Xuyun ZHANG Weiming LIU Li LI Yuwen LIU Zhongyuan ZHANG Guanfeng LIU Shengye PANG Xiaolong XU Lianyong QI; supported in part by National Natural Science Foundation of China(Grant No.62372242)。; Knowledge graphs(KGs)effectively mitigate data sparsity in recommendation systems(RSs)by providing valuable auxiliary information[1].However,traditional centralized KG-based RSs increase the risk of user privacy leaka...; 关键词：two stage information loop recommendation systems rss model training personalized privacy preserving recommendation systems federated knowledge graph decentralized data knowledge graphs kgs effectively knowledge graphs

Exploring & exploiting high-order graph structure for sparse knowledge graph completion: 《Frontiers of Computer Science》2025年第2期31-42,共12页Tao HE Ming LIU Yixin CAO Zekun WANG Zihao ZHENG Bing QIN; supported by the National Key R&D Program of China(2022YFF0903301);the National Natural Science Foundation of China(Grant Nos.U22B2059,61976073,62276083);the Shenzhen Foundational Research Funding(JCYJ20200109113441941);the Major Key Project of PCL(PCL2021A06).; Sparse Knowledge Graph(KG)scenarios pose a challenge for previous Knowledge Graph Completion(KGC)methods,that is,the completion performance decreases rapidly with the increase of graph sparsity.This problem is also ex...; 关键词：knowledge graph completion graph neural networks reinforcement learning

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