Papers Triple Classification
“Triple Classification” 태그가 달린 논문 51편 · 필터 해제
Differentiating Concepts and Instances for Knowledge Graph Embedding
Concepts, which represent a group of different instances sharing common properties, are essential information in knowledge representation. Most conventional knowledge embedding methods encode both entities (concepts and …
Graph EmbeddingKnowledge Graph EmbeddingKnowledge GraphsLink Prediction+1DOLORES: Deep Contextualized Knowledge Graph Embeddings
We introduce a new method DOLORES for learning knowledge graph embeddings that effectively captures contextual cues and dependencies among entities and relations. First, we note that short paths on knowledge graphs compr…
Knowledge Graph EmbeddingsKnowledge GraphsLink PredictionPrediction+3Accurate Text-Enhanced Knowledge Graph Representation Learning
Previous representation learning techniques for knowledge graph representation usually represent the same entity or relation in different triples with the same representation, without considering the ambiguity of relatio…
General ClassificationGraph Representation LearningKnowledge GraphsLink Prediction+3A Multimodal Translation-Based Approach for Knowledge Graph Representation Learning
Current methods for knowledge graph (KG) representation learning focus solely on the structure of the KG and do not exploit any kind of external information, such as visual and linguistic information corresponding to the…
Graph Representation LearningInformation RetrievalKnowledge Graph CompletionKnowledge Graphs+4Does William Shakespeare REALLY Write Hamlet? Knowledge Representation Learning with Confidence
Knowledge graphs (KGs), which could provide essential relational information between entities, have been widely utilized in various knowledge-driven applications. Since the overall human knowledge is innumerable that sti…
Knowledge Graph CompletionKnowledge GraphsRepresentation LearningTriple ClassificationImage-embodied Knowledge Representation Learning
Entity images could provide significant visual information for knowledge representation learning. Most conventional methods learn knowledge representations merely from structured triples, ignoring rich visual information…
General ClassificationKnowledge Graph CompletionRepresentation LearningTriple ClassificationKnowledge Representation via Joint Learning of Sequential Text and Knowledge Graphs
Textual information is considered as significant supplement to knowledge representation learning (KRL). There are two main challenges for constructing knowledge representations from plain texts: (1) How to take full adva…
InformativenessKnowledge GraphsLink PredictionRepresentation Learning+2Neighborhood Mixture Model for Knowledge Base Completion
Knowledge bases are useful resources for many natural language processing tasks, however, they are far from complete. In this paper, we define a novel entity representation as a mixture of its neighborhood in the knowled…
General ClassificationKnowledge Base CompletionmodelPrediction+2Probabilistic Reasoning via Deep Learning: Neural Association Models
In this paper, we propose a new deep learning approach, called neural association model (NAM), for probabilistic reasoning in artificial intelligence. We propose to use neural networks to model association between any tw…
Deep LearningNatural Language InferenceNatural Language UnderstandingTransfer Learning+1Knowlege Graph Embedding by Flexible Translation
Knowledge graph embedding refers to projecting entities and relations in knowledge graph into continuous vector spaces. State-of-the-art methods, such as TransE, TransH, and TransR build embeddings by treating relation a…
General ClassificationGraph EmbeddingKnowledge Graph EmbeddingLink Prediction+3Learning Entity and Relation Embeddings for Knowledge Graph Completion
Knowledge graph completion aims to perform link prediction between entities. In this paper, we consider the approach of knowledge graph embeddings. Recently, models such as TransE and TransH build entity and relation emb…
Knowledge Graph CompletionKnowledge Graph EmbeddingsLink PredictionRelation+1