Results 51 to 60 of about 35,565 (288)

Contextual language models for knowledge graph completion [PDF]

, 2021
Knowledge Graphs (KGs) have become the backbone of various machine learning based applications over the past decade. However, the KGs are often incomplete and inconsistent. Several representation learning based approaches have been introduced to complete the missing information in KGs. Besides, Neural Language Models (NLMs) have gained huge momentum in
Biswas, Russa, Sofronova, Radina, Alam, Mehwish, Sack, Harald   +3 more
openaire   +3 more sources

Normalizing Flow-based Neural Process for Few-Shot Knowledge Graph Completion

, 2023
Knowledge graphs (KGs), as a structured form of knowledge representation, have been widely applied in the real world. Recently, few-shot knowledge graph completion (FKGC), which aims to predict missing facts for unseen relations with few-shot associated ...
Li, YF, Haffari, G, Luo, L, Pan, S
core   +1 more source

Improved Knowledge Graph Completion Method for Capsule Network [PDF]

Jisuanji gongcheng, 2020
In order to complete the missing relations between entities of knowledge graph,this paper proposes an improved knowledge graph completion method for capsule network.First,the triplets are presented as a 3-column matrix,which is convolved with multiple ...
WANG Weimei, SHI Yimin, LI Guanyu
doaj   +1 more source

Collective Knowledge Graph Completion with Mutual Knowledge Distillation

CoRR, 2023
Knowledge graph completion (KGC), the task of predicting missing information based on the existing relational data inside a knowledge graph (KG), has drawn significant attention in recent years. However, the predictive power of KGC methods is often limited by the completeness of the existing knowledge graphs from different sources and languages.
Weihang Zhang, Ovidiu Serban, Jiahao Sun, Yike Guo   +3 more
openaire   +2 more sources

Multi-level Fusion Knowledge Graph Completion Model [PDF]

Jisuanji kexue yu tansuo
Knowledge graph completion aims to expand and enhance knowledge graphs by predicting missing triples. Multi-modal knowledge graph completion integrates entity ontology information such as entity descriptions, entity images, and entity attributes to ...
YE Zhihong, WU Yunbing, DAI Sichong, ZENG Zhihong
doaj   +1 more source

RecKGC: Integrating Recommendation with Knowledge Graph Completion

, 2019
Both recommender systems and knowledge graphs can provide overall and detailed views on datasets, and each of them has been a hot research domain by itself.
Chen, Weitong, Zhong, Mingyang, Ma, Jingwei, Mingyang Zhong, Li, Xue, Xiaofang Zhou, Xue Li, Zhou, Xiaofang, Jingwei Ma, Jiahui Wen, Weitong Chen, Wen, Jiahui   +11 more
core   +2 more sources

Abstract Graphs and Abstract Paths for Knowledge Graph Completion [PDF]

Proceedings of the Eighth Joint Conference on Lexical and Computational Semantics (*SEM 2019), 2019
Knowledge graphs, which provide numerous facts in a machine-friendly format, are incomplete. Information that we induce from such graphs – e.g. entity embeddings, relation representations or patterns – will be affected by the imbalance in the information captured in the graph – by biasing representations, or causing us to miss potential patterns.
Vivi Nastase, Bhushan Kotnis
openaire   +1 more source

Medical Knowledge Graph Completion Based on Word Embeddings

Information, 2022
The aim of Medical Knowledge Graph Completion is to automatically predict one of three parts (head entity, relationship, and tail entity) in RDF triples from medical data, mainly text data.
Mingxia Gao, Jianguo Lu, Furong Chen
doaj   +1 more source

Graph Attention Networks With Local Structure Awareness for Knowledge Graph Completion

IEEE Access, 2020
Graph neural networks have been proven to be very effective for representation learning of knowledge graphs. Recent methods such as SACN and CompGCN, have achieved the most advanced results in knowledge graph completion.
Kexi Ji, Bei Hui, Guangchun Luo
doaj   +1 more source

Knowledge Graph Entity Type Completion Based on Neighborhood Aggregation and CNN [PDF]

Jisuanji gongcheng, 2023
Existing entity type completion models of the knowledge graph solve the entity types missing in the knowledge graph by modeling entities and entity types.However, they do not effectively use the relationships between entities, which results in the poor ...
ZOU Changlong, AN Jingmin, LI Guanyu
doaj   +1 more source