Papers Knowledge Base Completion
“Knowledge Base Completion” 태그가 달린 논문 156편 · 필터 해제
Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs
Knowledge graphs offer a structured representation of real-world entities and their relationships, enabling a wide range of applications from information retrieval to automated reasoning. In this paper, we conduct a syst…
Graph Neural NetworkInformation RetrievalKnowledge Base CompletionKnowledge Graph Completion+2Large Language Model-Enhanced Symbolic Reasoning for Knowledge Base Completion
Integrating large language models (LLMs) with rule-based reasoning offers a powerful solution for improving the flexibility and reliability of Knowledge Base Completion (KBC). Traditional rule-based KBC methods offer ver…
DiversityHallucinationKnowledge Base CompletionLanguage Modeling+2Extracting triples from dialogues for conversational social agents
Obtaining an explicit understanding of communication within a Hybrid Intelligence collaboration is essential to create controllable and transparent agents. In this paper, we describe a number of Natural Language Understa…
Knowledge Base CompletionNatural Language UnderstandingNegationKnowledge Graphs: The Future of Data Integration and Insightful Discovery
Knowledge graphs are an efficient method for representing and connecting information across various concepts, useful in reasoning, question answering, and knowledge base completion tasks. They organize data by linking po…
ChatbotData IntegrationKnowledge Base CompletionKnowledge Graphs+3DELE: Deductive $\mathcal{EL}^{++} \thinspace $ Embeddings for Knowledge Base Completion
Ontology embeddings map classes, relations, and individuals in ontologies into $\mathbb{R}^n$, and within $\mathbb{R}^n$ similarity between entities can be computed or new axioms inferred. For ontologies in the Descripti…
Knowledge Base CompletionOntology EmbeddingDo LLMs Really Adapt to Domains? An Ontology Learning Perspective
Large Language Models (LLMs) have demonstrated unprecedented prowess across various natural language processing tasks in various application domains. Recent studies show that LLMs can be leveraged to perform lexical sema…
Knowledge Base CompletionRelation ExtractionEfficient Parallel Multi-Hop Reasoning: A Scalable Approach for Knowledge Graph Analysis
Multi-hop reasoning (MHR) is a process in artificial intelligence and natural language processing where a system needs to make multiple inferential steps to arrive at a conclusion or answer. In the context of knowledge g…
Knowledge Base CompletionKnowledge GraphsLink PredictionNavigate+1Pre-training and Diagnosing Knowledge Base Completion Models
In this work, we introduce and analyze an approach to knowledge transfer from one collection of facts to another without the need for entity or relation matching. The method works for both canonicalized knowledge bases a…
General KnowledgeKnowledge Base CompletionKnowledge Graph EmbeddingsTransfer Learning+1Evaluating the Knowledge Base Completion Potential of GPT
Structured knowledge bases (KBs) are an asset for search engines and other applications, but are inevitably incomplete. Language models (LMs) have been proposed for unsupervised knowledge base completion (KBC), yet, thei…
Knowledge Base CompletionKnowledge Base Completion for Long-Tail Entities
Despite their impressive scale, knowledge bases (KBs), such as Wikidata, still contain significant gaps. Language models (LMs) have been proposed as a source for filling these gaps. However, prior works have focused on p…
Knowledge Base CompletionRetrievalPredicting affinity ties in a surname network
From administrative registers of last names in Santiago, Chile, we create a surname affinity network that encodes socioeconomic data. This network is a multi-relational graph with nodes representing surnames and edges re…
Knowledge Base CompletionLattice-preserving $\mathcal{ALC}$ ontology embeddings with saturation
Generating vector representations (embeddings) of OWL ontologies is a growing task due to its applications in predicting missing facts and knowledge-enhanced learning in fields such as bioinformatics. The underlying sema…
DescriptiveKnowledge Base CompletionOntology EmbeddingEvaluating Language Models for Knowledge Base Completion
Structured knowledge bases (KBs) are a foundation of many intelligent applications, yet are notoriously incomplete. Language models (LMs) have recently been proposed for unsupervised knowledge base completion (KBC), yet,…
Knowledge Base CompletionCausal Lifting and Link Prediction
Existing causal models for link prediction assume an underlying set of inherent node factors -- an innate characteristic defined at the node's birth -- that governs the causal evolution of links in the graph. In some cau…
Graph Neural NetworkKnowledge Base CompletionLink PredictionPredictionZeroKBC: A Comprehensive Benchmark for Zero-Shot Knowledge Base Completion
Knowledge base completion (KBC) aims to predict the missing links in knowledge graphs. Previous KBC tasks and approaches mainly focus on the setting where all test entities and relations have appeared in the training set…
Knowledge Base CompletionKnowledge GraphsQuery-Driven Knowledge Base Completion using Multimodal Path Fusion over Multimodal Knowledge Graph
Over the past few years, large knowledge bases have been constructed to store massive amounts of knowledge. However, these knowledge bases are highly incomplete, for example, over 70% of people in Freebase have no known …
Knowledge Base CompletionKnowledge GraphsQuestion AnsweringKnowledge Base Completion using Web-Based Question Answering and Multimodal Fusion
Over the past few years, large knowledge bases have been constructed to store massive amounts of knowledge. However, these knowledge bases are highly incomplete. To solve this problem, we propose a web-based question ans…
Knowledge Base CompletionQuestion AnsweringInstance-based Learning for Knowledge Base Completion
In this paper, we propose a new method for knowledge base completion (KBC): instance-based learning (IBL). For example, to answer (Jill Biden, lived city,? ), instead of going directly to Washington D.C., our goal is to …
Knowledge Base CompletionmOKB6: A Multilingual Open Knowledge Base Completion Benchmark
Automated completion of open knowledge bases (Open KBs), which are constructed from triples of the form (subject phrase, relation phrase, object phrase), obtained via open information extraction (Open IE) system, are use…
coreference-resolutionCoreference ResolutionKnowledge Base CompletionOpen Information ExtractionRobust and Efficient Imbalanced Positive-Unlabeled Learning with Self-supervision
Learning from positive and unlabeled (PU) data is a setting where the learner only has access to positive and unlabeled samples while having no information on negative examples. Such PU setting is of great importance in …
Knowledge Base CompletionMedical DiagnosisRepresentation LearningSelf-Supervised Learning