Papers Knowledge Graph Completion
“Knowledge Graph Completion” 태그가 달린 논문 541편 · 필터 해제
Challenging the Assumption of Structure-based embeddings in Few- and Zero-shot Knowledge Graph Completion
In this paper, we report experiments on Few- and Zero-shot Knowledge Graph completion, where the objective is to add missing relational links between entities into an existing Knowledge Graph with few or no previous exam…
DescriptiveKnowledge Graph CompletionTransfer LearningTowards Bengali WordNet Enrichment using Knowledge Graph Completion Techniques
WordNet serves as a very essential knowledge source for various downstream Natural Language Processing (NLP) tasks. Since this is a human-curated resource, building such a resource is very cumbersome and time-consuming. …
Knowledge Graph CompletionEnriching Hindi WordNet Using Knowledge Graph Completion Approach
Even though the use of WordNet in the Natural Language Processing domain is unquestionable, creating and maintaining WordNet is a cumbersome job and it is even difficult for low resource languages like Hindi. In this stu…
Knowledge Graph CompletionRelphormer: Relational Graph Transformer for Knowledge Graph Representations
Transformers have achieved remarkable performance in widespread fields, including natural language processing, computer vision and graph mining. However, vanilla Transformer architectures have not yielded promising impro…
General KnowledgeGraph MiningGraph Representation LearningKnowledge Graph Completion+4Are Message Passing Neural Networks Really Helpful for Knowledge Graph Completion?
Knowledge graphs (KGs) facilitate a wide variety of applications. Despite great efforts in creation and maintenance, even the largest KGs are far from complete. Hence, KG completion (KGC) has become one of the most cruci…
Knowledge Graph CompletionKnowledge GraphsA Birds Eye View on Knowledge Graph Embeddings, Software Libraries, Applications and Challenges
In recent years, Knowledge Graph (KG) development has attracted significant researches considering the applications in web search, relation prediction, natural language processing, information retrieval, question answeri…
Information RetrievalKnowledge Graph CompletionKnowledge Graph EmbeddingsKnowledge Graphs+4Re-thinking Knowledge Graph Completion Evaluation from an Information Retrieval Perspective
Knowledge graph completion (KGC) aims to infer missing knowledge triples based on known facts in a knowledge graph. Current KGC research mostly follows an entity ranking protocol, wherein the effectiveness is measured by…
Information RetrievalKnowledge Graph CompletionRetrievalHybrid Transformer with Multi-level Fusion for Multimodal Knowledge Graph Completion
Multimodal Knowledge Graphs (MKGs), which organize visual-text factual knowledge, have recently been successfully applied to tasks such as information retrieval, question answering, and recommendation system. Since most …
Information RetrievalKnowledge Graph CompletionKnowledge GraphsLink Prediction+4Positive-Unlabeled Learning with Adversarial Data Augmentation for Knowledge Graph Completion
Most real-world knowledge graphs (KG) are far from complete and comprehensive. This problem has motivated efforts in predicting the most plausible missing facts to complete a given KG, i.e., knowledge graph completion (K…
Data AugmentationKnowledge Graph CompletionKnowledge GraphsWorld KnowledgeDo Pre-trained Models Benefit Knowledge Graph Completion? A Reliable Evaluation and a Reasonable Approach
In recent years, pre-trained language models (PLMs) have been shown to capture factual knowledge from massive texts, which encourages the proposal of PLM-based knowledge graph completion (KGC) models. However, these mode…
Knowledge Graph CompletionLink PredictionTempCaps: A Capsule Network-based Embedding Model for Temporal Knowledge Graph Completion
Temporal knowledge graphs store the dynamics of entities and relations during a time period. However, typical temporal knowledge graphs often suffer from incomplete dynamics with missing facts in real-world scenarios. He…
Entity EmbeddingsKnowledge Graph CompletionKnowledge GraphsTemporal Knowledge Graph CompletionLearning to Borrow -- Relation Representation for Without-Mention Entity-Pairs for Knowledge Graph Completion
Prior work on integrating text corpora with knowledge graphs (KGs) to improve Knowledge Graph Embedding (KGE) have obtained good performance for entities that co-occur in sentences in text corpora. Such sentences (textua…
Entity EmbeddingsGraph EmbeddingKnowledge Graph CompletionKnowledge Graph Embedding+4TranSHER: Translating Knowledge Graph Embedding with Hyper-Ellipsoidal Restriction
Knowledge graph embedding methods are important for the knowledge graph completion (or link prediction) task. One existing efficient method, PairRE, leverages two separate vectors to model complex relations (i.e., 1-to-N…
Graph EmbeddingKnowledge Graph CompletionKnowledge Graph EmbeddingKnowledge Graphs+3Temporal Knowledge Graph Reasoning with Low-rank and Model-agnostic Representations
Temporal knowledge graph completion (TKGC) has become a popular approach for reasoning over the event and temporal knowledge graphs, targeting the completion of knowledge with accurate but missing information. In this co…
Graph EmbeddingKnowledge Graph CompletionKnowledge Graph EmbeddingKnowledge Graphs+2Multilingual Knowledge Graph Completion with Self-Supervised Adaptive Graph Alignment
Predicting missing facts in a knowledge graph (KG) is crucial as modern KGs are far from complete. Due to labor-intensive human labeling, this phenomenon deteriorates when handling knowledge represented in various langua…
Knowledge Graph CompletionLearning Relation-Specific Representations for Few-shot Knowledge Graph Completion
Recent years have witnessed increasing interest in few-shot knowledge graph completion (FKGC), which aims to infer unseen query triples for a few-shot relation using a few reference triples about the relation. The primar…
Entity EmbeddingsKnowledge Graph CompletionRelationSequence-to-Sequence Knowledge Graph Completion and Question Answering
Knowledge graph embedding (KGE) models represent each entity and relation of a knowledge graph (KG) with low-dimensional embedding vectors. These methods have recently been applied to KG link prediction and question answ…
DecoderGraph EmbeddingKnowledge Graph CompletionKnowledge Graph Embedding+3ECOLA: Enhanced Temporal Knowledge Embeddings with Contextualized Language Representations
Since conventional knowledge embedding models cannot take full advantage of the abundant textual information, there have been extensive research efforts in enhancing knowledge embedding using texts. However, existing enh…
Graph EmbeddingKnowledge Graph CompletionKnowledge Graph EmbeddingKnowledge Graphs+2RotateQVS: Representing Temporal Information as Rotations in Quaternion Vector Space for Temporal Knowledge Graph Completion
Temporal factors are tied to the growth of facts in realistic applications, such as the progress of diseases and the development of political situation, therefore, research on Temporal Knowledge Graph (TKG) attracks much…
Knowledge Graph CompletionLink PredictionRelationRepresentation Learning+1SimKGC: Simple Contrastive Knowledge Graph Completion with Pre-trained Language Models
Knowledge graph completion (KGC) aims to reason over known facts and infer the missing links. Text-based methods such as KGBERT (Yao et al., 2019) learn entity representations from natural language descriptions, and have…
Contrastive LearningGraph EmbeddingKnowledge Graph CompletionLink Prediction