Interaction Embeddings for Prediction and Explanation in Knowledge Graphs
暂无分享,去创建一个
Wei Zhang | Huajun Chen | Abraham Bernstein | Bibek Paudel | Wen Zhang | Wei Zhang | A. Bernstein | B. Paudel | Huajun Chen | Wen Zhang
[1] Jason Weston,et al. Learning Structured Embeddings of Knowledge Bases , 2011, AAAI.
[2] Jason Weston,et al. Translating Embeddings for Modeling Multi-relational Data , 2013, NIPS.
[3] Fan Yang,et al. Differentiable Learning of Logical Rules for Knowledge Base Reasoning , 2017, NIPS.
[4] Jianfeng Gao,et al. Embedding Entities and Relations for Learning and Inference in Knowledge Bases , 2014, ICLR.
[5] Lizhen Qu,et al. STransE: a novel embedding model of entities and relationships in knowledge bases , 2016, NAACL.
[6] Zhiyuan Liu,et al. Learning Entity and Relation Embeddings for Knowledge Graph Completion , 2015, AAAI.
[7] Max Welling,et al. Modeling Relational Data with Graph Convolutional Networks , 2017, ESWC.
[8] Tim Weninger,et al. ProjE: Embedding Projection for Knowledge Graph Completion , 2016, AAAI.
[9] Fabian M. Suchanek,et al. Fast rule mining in ontological knowledge bases with AMIE+\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$+$$\end{docu , 2015, The VLDB Journal.
[10] Zhiyuan Liu,et al. Representation Learning of Knowledge Graphs with Hierarchical Types , 2016, IJCAI.
[11] Gerhard Weikum,et al. WWW 2007 / Track: Semantic Web Session: Ontologies ABSTRACT YAGO: A Core of Semantic Knowledge , 2022 .
[12] Jun Zhao,et al. Knowledge Graph Completion with Adaptive Sparse Transfer Matrix , 2016, AAAI.
[13] Evgeniy Gabrilovich,et al. A Review of Relational Machine Learning for Knowledge Graphs , 2015, Proceedings of the IEEE.
[14] Wen Zhang,et al. Knowledge Graph Embedding with Diversity of Structures , 2017, WWW.
[15] Volker Tresp,et al. Type-Constrained Representation Learning in Knowledge Graphs , 2015, SEMWEB.
[16] Jun Zhao,et al. Knowledge Graph Embedding via Dynamic Mapping Matrix , 2015, ACL.
[17] Andrew McCallum,et al. Compositional Vector Space Models for Knowledge Base Completion , 2015, ACL.
[18] Li Guo,et al. Knowledge Base Completion Using Embeddings and Rules , 2015, IJCAI.
[19] Guillaume Bouchard,et al. Complex Embeddings for Simple Link Prediction , 2016, ICML.
[20] Huanbo Luan,et al. Modeling Relation Paths for Representation Learning of Knowledge Bases , 2015, EMNLP.
[21] Xin Jiang,et al. Neural Generative Question Answering , 2015, IJCAI.
[22] Praveen Paritosh,et al. Freebase: a collaboratively created graph database for structuring human knowledge , 2008, SIGMOD Conference.
[23] Tat-Seng Chua,et al. TEM: Tree-enhanced Embedding Model for Explainable Recommendation , 2018, WWW.
[24] George A. Miller,et al. WordNet: A Lexical Database for English , 1995, HLT.
[25] Danqi Chen,et al. Observed versus latent features for knowledge base and text inference , 2015, CVSC.
[26] Fernando Gomez,et al. Automatically acquiring a semantic network of related concepts , 2010, CIKM '10.
[27] Jason Weston,et al. A semantic matching energy function for learning with multi-relational data , 2013, Machine Learning.
[28] James L. McClelland,et al. Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations , 1986 .
[29] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[30] Nitish Srivastava,et al. Dropout: a simple way to prevent neural networks from overfitting , 2014, J. Mach. Learn. Res..
[31] Zhen Wang,et al. Knowledge Graph Embedding by Translating on Hyperplanes , 2014, AAAI.
[32] Danqi Chen,et al. Reasoning With Neural Tensor Networks for Knowledge Base Completion , 2013, NIPS.
[33] Tom M. Mitchell,et al. Random Walk Inference and Learning in A Large Scale Knowledge Base , 2011, EMNLP.
[34] Nicolas Le Roux,et al. A latent factor model for highly multi-relational data , 2012, NIPS.
[35] Yiming Yang,et al. Analogical Inference for Multi-relational Embeddings , 2017, ICML.
[36] Lorenzo Rosasco,et al. Holographic Embeddings of Knowledge Graphs , 2015, AAAI.
[37] Antoine Bordes,et al. Composing Relationships with Translations , 2015, EMNLP.
[38] Jun Zhao,et al. Learning to Represent Knowledge Graphs with Gaussian Embedding , 2015, CIKM.
[39] Reinhard Heckel,et al. Scalable and Interpretable Product Recommendations via Overlapping Co-Clustering , 2016, 2017 IEEE 33rd International Conference on Data Engineering (ICDE).
[40] Han Xiao,et al. TransG : A Generative Model for Knowledge Graph Embedding , 2015, ACL.
[41] Heiko Paulheim,et al. RDF2Vec: RDF Graph Embeddings for Data Mining , 2016, SEMWEB.
[42] Hans-Peter Kriegel,et al. A Three-Way Model for Collective Learning on Multi-Relational Data , 2011, ICML.
[43] Yoshua Bengio,et al. Understanding the difficulty of training deep feedforward neural networks , 2010, AISTATS.
[44] Geoffrey E. Hinton,et al. Distributed Representations , 1986, The Philosophy of Artificial Intelligence.