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检索条件"主题词=Knowledge Graph embedding"
569 条 记 录,以下是491-500 订阅
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Decoupled knowledge Propagation Network and Sampling Strategies for Recommendation System  27
Decoupled Knowledge Propagation Network and Sampling Strateg...
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27th International Conference on Technologies and Applications of Artificial Intelligence (TAAI)
作者: Kuo, Zhen-Yuan Lin, Bor-Shen Natl Taiwan Univ Sci & Technol Dept Informat Management Taipei Taiwan
State-of-the-art knowledge-graph-based models, such as RippleNet and CKAN, have been successfully applied to recommendation systems. These models make use of knowledge graph to expand the entity information, which is ... 详细信息
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Effective Use of BERT in graph embeddings for Sparse knowledge graph Completion  22
Effective Use of BERT in Graph Embeddings for Sparse Knowled...
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37th Annual ACM Symposium on Applied Computing
作者: Liu, Xinglan Hussain, Hussain Razouk, Houssam Kern, Roman Know Ctr GmbH Graz Austria Graz Univ Technol Graz Austria
graph embedding methods have emerged as effective solutions for knowledge graph completion. However, such methods are typically tested on benchmark datasets such as Freebase, but show limited performance when applied ... 详细信息
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NeuralKG: An Open Source Library for Diverse Representation Learning of knowledge graphs  22
NeuralKG: An Open Source Library for Diverse Representation ...
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45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)
作者: Zhang, Wen Chen, Xiangnan Yao, Zhen Chen, Mingyang Zhu, Yushan Yu, Hongtao Huang, Yufeng Xu, Yajing Zhang, Ningyu Xu, Zezhong Yuan, Zonggang Xiong, Feiyu Chen, Huajun Zhejiang Univ Sch Software Technol Hangzhou Zhejiang Peoples R China Zhejiang Univ Coll Comp Sci & Technol Hangzhou Zhejiang Peoples R China Huawei Technol Co Ltd Shenzhen Guangdong Peoples R China Alibaba Grp Hangzhou Zhejiang Peoples R China Alibaba Zhejiang Univ Joint Inst Frontier Technol ZJU Hangzhou Global Sci & Technol Innovat Ctr Hangzhou Zhejiang Peoples R China
NeuralKG is an open-source Python-based library for diverse representation learning of knowledge graphs. It implements three kinds of knowledge graph embedding (KGE) methods, including conventional KGEs, GNN-based KGE... 详细信息
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Leveraging the Power of Echo State Network for Enhanced Temporal knowledge graph Reasoning
Leveraging the Power of Echo State Network for Enhanced Temp...
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International Joint Conference on Neural Networks (IJCNN)
作者: Sun, Yi Wang, Zhe Wang, Kewen Griffith Univ Sch Informat & Commun Technol Brisbane Qld Australia
Temporal knowledge graphs (TKG) reasoning has emerged as a powerful methodology for prediction in various domains. Unlike traditional knowledge graphs(KG), TKGs introduce a critical time dimension to the graph structu... 详细信息
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knowledge Augmented Inference Network for Natural Language Inference  3rd
Knowledge Augmented Inference Network for Natural Language I...
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3rd China Conference on knowledge graph and Semantic Computing (CCKS)
作者: Jiang, Shan Li, Bohan Liu, Chunhua Yu, Dong Beijing Adv Innovat Language Resources BLCU Beijing Peoples R China Beijing Language & Culture Univ Beijing Peoples R China
This paper proposes a knowledge Augmented Inference Network (K- AIN) that can effectively incorporate external knowledge into existing neural network models on Natural Language Inference (NLI) task. Different from pre... 详细信息
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Multi-task knowledge graph Representations via Residual Functions  1
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26th Pacific-Asia Conference on knowledge Discovery and Data Mining (PAKDD)
作者: Krishnan, Adit Das, Mahashweta Bendre, Mangesh Wang, Fei Yang, Hao Sundaram, Hari Univ Illinois Champaign IL 61820 USA Visa Res Palo Alto CA USA
In this paper, we propose MuTATE, a Multi-Task Augmented approach to learn Transferable embeddings of knowledge graphs. Previous knowledge graph representation techniques either employ task-agnostic geometric hypothes... 详细信息
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Link Prediction Using Multi Part embeddings  16th
Link Prediction Using Multi Part Embeddings
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16th International Extended Semantic Web Conference (ESWC)
作者: Mohamed, Sameh K. Novacek, Vit Data Sci Inst Galway Ireland Insight Ctr Data Analyt Galway Ireland Natl Univ Ireland Galway Galway Ireland
knowledge graph embeddings models are widely used to provide scalable and efficient link prediction for knowledge graphs. They use different techniques to model embeddings interactions, where their tensor factorisatio... 详细信息
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KIDNet: A knowledge-Aware Neural Network Model for Academic Performance Prediction
KIDNet: A Knowledge-Aware Neural Network Model for Academic ...
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IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)
作者: Tang, Tao Hou, Jie Guo, Teng Bai, Xiaomei Tian, Xue Hoshyar, Azadeh Noori Federat Univ Australia Sch Engn IT & Phys Sci Ballarat Vic Australia Dalian Univ Technol Sch Software Dalian Liaoning Peoples R China Anshan Normal Univ Comp Ctr Anshan Liaoning Peoples R China Univ Tasmania Sch Arts Law & Educ Launceston Tas Australia Federat Univ Australia Sch Engn IT & Phys Sci Brisbane Qld Australia
Academic performance prediction and analysis in educational data mining is meaningful for instructors to know the student's ongoing learning status, and also provide appropriate help to students as early as possib... 详细信息
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Entity Alignment Between knowledge graphs Using Entity Type Matching  14th
Entity Alignment Between Knowledge Graphs Using Entity Type ...
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14th International Conference on knowledge Science, Engineering, and Management (KSEM)
作者: Song, Xiuting Zhang, Han Bai, Luyi Northeastern Univ Qinhuangdao Sch Comp & Commun Engn Qinhuangdao 066004 Hebei Peoples R China
The task of entity alignment between knowledge graphs (KGs) aims to find entities in two knowledge graphs that represent the same real-world entity. Recently, embedding-based entity alignment methods get extended atte... 详细信息
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A Physical embedding Model for knowledge graphs  1
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9th Joint International Semantic Technology Conference (JIST)
作者: Demir, Caglar Ngomo, Axel-Cyrille Ngonga Paderborn Univ DICE Res Grp D-33098 Paderborn Germany
knowledge graph embedding methods learn continuous vector representations for entities in knowledge graphs and have been used successfully in a large number of applications. We present a novel and scalable paradigm fo... 详细信息
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