Results 51 to 60 of about 8,119,426 (288)
Type-enhanced Inductive Knowledge Graph Completion
, 2023 Inductive knowledge graph completion has gained significant attention due to the dynamic nature of entities and facts in knowledge graphs (KGs). The goal of this task is to predict missing links between entities that are unseen during training.
Ma, S, Wang, Z, Wang, K, Zhuang, Z
core
S-DBpedia: A benchmark dataset for spatial knowledge graph completion
, 2022 S-DBpedia is a collection of knowledge graph completion benchmark datasets extracted from DBpedia, with special focus on spatial information.
Mao,chaoyuan
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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
Pre-training Transformers for Knowledge Graph Completion
CoRR, 2023 Learning transferable representation of knowledge graphs (KGs) is challenging due to the heterogeneous, multi-relational nature of graph structures. Inspired by Transformer-based pretrained language models' success on learning transferable representation for texts, we introduce a novel inductive KG representation model (iHT) for KG completion by large ...
Sanxing Chen +5 more
openaire +2 more sources
Joint Multilingual Knowledge Graph Completion and Alignment
, 2022 Knowledge graph (KG) alignment and completion are usually treated as two independent tasks. While recent work has leveraged entity and relation alignments from multiple KGs, such as alignments between multilingual KGs with common entities and relations ...
Nguyen, DQ +5 more
core
Knowledge Graph Completion with Knowledge Enhancement and Contrastive Learning [PDF]
Jisuanji gongchengKnowledge Graph Completion(KGC) is an important means of improving the quality of KGs. Existing methods for KGC are mainly divided into structure- and description-based methods.
Juan LIU, Youxiang DUAN, Yuxi LU, Lu ZHANG
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Structured Self-Supervised Pretraining for Commonsense Knowledge Graph Completion
Transactions of the Association for Computational Linguistics, 2021 To develop commonsense-grounded NLP applications, a comprehensive and accurate commonsense knowledge graph (CKG) is needed. It is time-consuming to manually construct CKGs and many research efforts have been devoted to the automatic construction of CKGs.
Jiayuan Huang +4 more
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A Few-Shot Knowledge Graph Completion Model With Neighbor Filter and Affine Attention
IEEE AccessIn recent times, extensive scholarly focus has been directed towards the knowledge graph completion (KGC) due to the large number of triples that perform well in training tasks. However, the relations of realistic knowledge graphs (KGs) usually have long-
Hongfang Gong, Yingjing Ding, Minyi Ma
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Knowledge graph completion for scholarly knowledge graph
Bulletin of Social Informatics Theory and ApplicationScholarly knowledge graph is a knowledge graph that is used to represent knowledge contained in scientific publication documents. The information we can find in a scientific publication document is as follows: author, institution, name of journal/conference, and research topic. A knowledge graph that has been built is usually still not perfect.
Taufiqurrahman Taufiqurrahman +2 more
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FEBS Letters, EarlyView.We present robust protocols for the preparation of supported lipid bilayers (SLBs) incorporating either Salmonella smooth LPS or outer membrane vesicles (OMVs). We use a combination of quartz crystal microbalance with dissipation (QCM‐D) and fluorescence microscopy to both characterize the SLBs of various compositions and to probe their interactions ...
Hudson P. Pace +6 more
wiley +1 more source