A Review of Relational Machine Learning for Knowledge Graphs
arXiv:1503.00759 · doi:10.1109/JPROC.2015.2483592
Abstract
Relational machine learning studies methods for the statistical analysis of relational, or graph-structured, data. In this paper, we provide a review of how such statistical models can be "trained" on large knowledge graphs, and then used to predict new facts about the world (which is equivalent to predicting new edges in the graph). In particular, we discuss two fundamentally different kinds of statistical relational models, both of which can scale to massive datasets. The first is based on latent feature models such as tensor factorization and multiway neural networks. The second is based on mining observable patterns in the graph. We also show how to combine these latent and observable models to get improved modeling power at decreased computational cost. Finally, we discuss how such statistical models of graphs can be combined with text-based information extraction methods for automatically constructing knowledge graphs from the Web. To this end, we also discuss Google's Knowledge Vault project as an example of such combination.
To appear in Proceedings of the IEEE
References in corpus (4)
Cited by in corpus (248)
- A Survey on Knowledge Graphs: Representation, Acquisition and Applications
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- PyTorch-BigGraph: A Large-scale Graph Embedding System
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- Graph signal processing for machine learning: A review and new perspectives
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- Knowledge Graphs in Manufacturing and Production: A Systematic Literature Review
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- Onto2Vec: joint vector-based representation of biological entities and their ontology-based annotations
- Progresses and Challenges in Link Prediction
- Bringing Light Into the Dark: A Large-scale Evaluation of Knowledge Graph Embedding Models Under a Unified Framework
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- Machine Knowledge: Creation and Curation of Comprehensive Knowledge Bases
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- Neural Bellman-Ford Networks: A General Graph Neural Network Framework for Link Prediction
- If I Hear You Correctly: Building and Evaluating Interview Chatbots with Active Listening Skills
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- Know-Evolve: Deep Temporal Reasoning for Dynamic Knowledge Graphs
- IMF: Interactive Multimodal Fusion Model for Link Prediction
- Applications of knowledge graphs for food science and industry
- Probabilistic Logic Neural Networks for Reasoning
- PyKEEN 1.0: A Python Library for Training and Evaluating Knowledge Graph Embeddings
- SE-KGE: A Location-Aware Knowledge Graph Embedding Model for Geographic Question Answering and Spatial Semantic Lifting
- Construction of Knowledge Graphs: State and Challenges
- On the representation and embedding of knowledge bases beyond binary relations
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- Differentially Private Federated Knowledge Graphs Embedding
- An Open-World Extension to Knowledge Graph Completion Models
- Putting An End to End-to-End: Gradient-Isolated Learning of Representations
- Query2box: Reasoning over Knowledge Graphs in Vector Space using Box Embeddings
- Graph Neural Networks with Continual Learning for Fake News Detection from Social Media
- Probabilistic Reasoning via Deep Learning: Neural Association Models
- Knowledge Transfer for Out-of-Knowledge-Base Entities: A Graph Neural Network Approach
- Learning Graph Representations with Embedding Propagation
- Measuring and Improving the Use of Graph Information in Graph Neural Networks
- Inductive Entity Representations from Text via Link Prediction
- Collaboration-Aware Graph Convolutional Network for Recommender Systems
- Causal Understanding of Fake News Dissemination on Social Media
- Contrastive Learning of Structured World Models
- CoKE: Contextualized Knowledge Graph Embedding
- Representation Learning for Dynamic Graphs: A Survey
- Inductive Relation Prediction by Subgraph Reasoning
- A Boxology of Design Patterns for Hybrid Learning and Reasoning Systems
- Analysis of the Impact of Negative Sampling on Link Prediction in Knowledge Graphs
- Trans4E: Link Prediction on Scholarly Knowledge Graphs
- Labeling Trick: A Theory of Using Graph Neural Networks for Multi-Node Representation Learning
- Knowledge-based Biomedical Data Science 2019
- Time2Vec: Learning a Vector Representation of Time
- Neighborhood Mixture Model for Knowledge Base Completion
- KBLRN : End-to-End Learning of Knowledge Base Representations with Latent, Relational, and Numerical Features
- Natural Language Processing for Information Extraction
- Canonical Tensor Decomposition for Knowledge Base Completion
- Review on Learning and Extracting Graph Features for Link Prediction
- Introduction to Neural Network based Approaches for Question Answering over Knowledge Graphs
- KBGAN: Adversarial Learning for Knowledge Graph Embeddings
- Bayesian Poisson Tucker Decomposition for Learning the Structure of International Relations
- What is Normal, What is Strange, and What is Missing in a Knowledge Graph: Unified Characterization via Inductive Summarization
- Relational Graph Convolutional Networks: A Closer Look
- Hashing-Accelerated Graph Neural Networks for Link Prediction
- On Event-Driven Knowledge Graph Completion in Digital Factories
- Meta-Graph: Few Shot Link Prediction via Meta Learning
- Deep Learning for Ontology Reasoning
- Ripple Knowledge Graph Convolutional Networks For Recommendation Systems
- Context-aware Path Ranking for Knowledge Base Completion
- An Interpretable Knowledge Transfer Model for Knowledge Base Completion
- A Review of Graph Neural Networks and Their Applications in Power Systems
- A Joint Communication and Computation Design for Semantic Wireless Communication with Probability Graph
- Lifelong and Interactive Learning of Factual Knowledge in Dialogues
- On the Use of ArXiv as a Dataset
- Does William Shakespeare REALLY Write Hamlet? Knowledge Representation Learning with Confidence
- Trust from the past: Bayesian Personalized Ranking based Link Prediction in Knowledge Graphs
- Iteratively Learning Embeddings and Rules for Knowledge Graph Reasoning
- Unstructured Text Enhanced Open-domain Dialogue System: A Systematic Survey
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- Aligning Robot and Human Representations
- Network-based Fake News Detection: A Pattern-driven Approach
- Fake News Early Detection: An Interdisciplinary Study
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- Probability Calibration for Knowledge Graph Embedding Models
- Metarobotics for Industry and Society: Vision, Technologies, and Opportunities
- Prediction of ESG Compliance using a Heterogeneous Information Network
- Interstellar: Searching Recurrent Architecture for Knowledge Graph Embedding
- Open-World Knowledge Graph Completion
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- NodePiece: Compositional and Parameter-Efficient Representations of Large Knowledge Graphs
- Modular Design Patterns for Hybrid Learning and Reasoning Systems: a taxonomy, patterns and use cases
- A Poisson Gamma Probabilistic Model for Latent Node-group Memberships in Dynamic Networks
- Investigating Extensions to Random Walk Based Graph Embedding
- Interpreting Embedding Models of Knowledge Bases: A Pedagogical Approach
- Neural Link Prediction with Walk Pooling
- Realistic Re-evaluation of Knowledge Graph Completion Methods: An Experimental Study
- HeteSpaceyWalk: A Heterogeneous Spacey Random Walk for Heterogeneous Information Network Embedding
- An Evaluation of Knowledge Graph Embeddings for Autonomous Driving Data: Experience and Practice
- Potentials of the Metaverse for Robotized Applications in Industry 4.0 and Industry 5.0
- Neural Graph Embedding Methods for Natural Language Processing
- Contextual Graph Attention for Answering Logical Queries over Incomplete Knowledge Graphs
- WordCraft: An Environment for Benchmarking Commonsense Agents
- TACAM: Topic And Context Aware Argument Mining
- Learning Attention-based Representations from Multiple Patterns for Relation Prediction in Knowledge Graphs
- Answering Visual-Relational Queries in Web-Extracted Knowledge Graphs
- Machine Learning with World Knowledge: The Position and Survey
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- Network Representation Learning: Consolidation and Renewed Bearing
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- Adaptive Attentional Network for Few-Shot Knowledge Graph Completion
- Benchmarking neural embeddings for link prediction in knowledge graphs under semantic and structural changes
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- NSCaching: Simple and Efficient Negative Sampling for Knowledge Graph Embedding
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- SCEF: A Support-Confidence-aware Embedding Framework for Knowledge Graph Refinement
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- Debate Dynamics for Human-comprehensible Fact-checking on Knowledge Graphs
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- Relational representation learning with spike trains
- The Tensor Brain: A Unified Theory of Perception, Memory and Semantic Decoding
- Convolutional Hypercomplex Embeddings for Link Prediction
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- Neural Variational Inference For Estimating Uncertainty in Knowledge Graph Embeddings
- Not all Embeddings are created Equal: Extracting Entity-specific Substructures for RDF Graph Embedding
- Multi-Relational Learning at Scale with ADMM
- Learning Structured Embeddings of Knowledge Graphs with Adversarial Learning Framework
- Extracting Novel Facts from Tables for Knowledge Graph Completion (Extended version)
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- TrQuery: An Embedding-based Framework for Recommanding SPARQL Queries
- Unsupervised Hierarchical Grouping of Knowledge Graph Entities
- Efficient Knowledge Graph Validation via Cross-Graph Representation Learning
- A Comparative Study on Structural and Semantic Properties of Sentence Embeddings
- The KEEN Universe: An Ecosystem for Knowledge Graph Embeddings with a Focus on Reproducibility and Transferability
- Convolutional Neural Knowledge Graph Learning
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- Metapaths guided Neighbors aggregated Network for?Heterogeneous Graph Reasoning
- Representation Learning for Words and Entities
- Knowledge Graphs and Machine Learning in biased C4I applications
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- Understanding in Artificial Intelligence
- Knowledge Generation -- Variational Bayes on Knowledge Graphs
- Network Representation Learning: From Traditional Feature Learning to Deep Learning
- HYPER^2: Hyperbolic Poincare Embedding for Hyper-Relational Link Prediction
- Link Prediction on N-ary Relational Data Based on Relatedness Evaluation
- Formalising Hypothesis Virtues in Knowledge Graphs: A General Theoretical Framework and its Validation in Literature-Based Discovery Experiments
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- Tracing Networks of Knowledge in the Digital Age
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- Background Knowledge Injection for Interpretable Sequence Classification
- A Critical Examination of RESCAL for Completion of Knowledge Bases with Transitive Relations
- Leveraging Semantics for Incremental Learning in Multi-Relational Embeddings
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- Parallax: Visualizing and Understanding the Semantics of Embedding Spaces via Algebraic Formulae
- Path Ranking with Attention to Type Hierarchies
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- Fast Haar Transforms for Graph Neural Networks
- A Non-commutative Bilinear Model for Answering Path Queries in Knowledge Graphs
- Knowledge Graphs and Knowledge Networks: The Story in Brief
- Automated Abstraction of Operation Processes from Unstructured Text for Simulation Modeling
- A Concept-Centered Hypertext Approach to Case-Based Retrieval
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- Feature Learning for Meta-Paths in Knowledge Graphs
- A Computational Theory for Life-Long Learning of Semantics
- Timestamping Documents and Beliefs
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- Inter-domain Multi-relational Link Prediction
- A Comparative Study of Distributional and Symbolic Paradigms for Relational Learning
- Pre and Post Counting for Scalable Statistical-Relational Model Discovery
- A Probabilistic Framework for Knowledge Graph Data Augmentation
- DAGSurv: Directed Acyclic Graph Based Survival Analysis Using Deep Neural Networks
- Adversarial Attacks on Knowledge Graph Embeddings via Instance Attribution Methods