Results 91 to 100 of about 468,662 (346)
One-Shot Relational Learning for Knowledge Graphs
, 2018 Knowledge graphs (KGs) are the key components of various natural language processing applications. To further expand KGs' coverage, previous studies on knowledge graph completion usually require a large number of training instances for each relation ...
Chang, Shiyu +4 more
core +1 more source
Molecular Oncology, EarlyView.Generation of two normal and tumour (cancerous) paired human cell lines using an established tissue culture technique and their characterisation is described. Cell lines were characterised at cellular, protein, chromosome and gene expression levels and for HPV status.
Simon Broad +12 more
wiley +1 more source
ShallowBKGC: a BERT-enhanced shallow neural network model for knowledge graph completion [PDF]
PeerJ Computer ScienceKnowledge graph completion aims to predict missing relations between entities in a knowledge graph. One of the effective ways for knowledge graph completion is knowledge graph embedding.
Ningning Jia, Cuiyou Yao
doaj +2 more sources
MLSFF: Multi-level structural features fusion for multi-modal knowledge graph completion
Mathematical Biosciences and Engineering, 2023 With the rise of multi-modal methods, multi-modal knowledge graphs have become a better choice for storing human knowledge. However, knowledge graphs often suffer from the problem of incompleteness due to the infinite and constantly updating nature of ...
Hanming Zhai +4 more
doaj +1 more source
Temporal knowledge graph completion based on product space and contrastive learning of commonsense
Journal of Intelligence and Information SystemsStatic knowledge graph completion (KGC) has made significant progress in the field of artificial intelligence. However, knowledge is time-sensitive, thus the introduction of Temporal Knowledge Graph Completion (TKGC) is necessary to accurately reflect ...
Zhenghao Chen, Jianbin Wu
semanticscholar +1 more source
Collective Knowledge Graph Completion with Mutual Knowledge Distillation
, 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.
Zhang, Weihang +3 more
openaire +2 more sources
Does William Shakespeare REALLY Write Hamlet? Knowledge Representation Learning with Confidence
, 2018 Knowledge graphs (KGs), which could provide essential relational information between entities, have been widely utilized in various knowledge-driven applications.
Lin, Fen +3 more
core +1 more source
Molecular Oncology, EarlyView.The cancer problem is increasing globally with projections up to the year 2050 showing unfavourable outcomes in terms of incidence and cancer‐related deaths. The main challenges are prevention, improved therapeutics resulting in increased cure rates and enhanced health‐related quality of life.
Ulrik Ringborg +43 more
wiley +1 more source
Hyperbolic Knowledge Graph Embeddings for Knowledge Base Completion [PDF]
, 2020 Learning embeddings of entities and relations existing in knowledge bases allows the discovery of hidden patterns in them. In this work, we examine the contribution of geometrical space to the task of knowledge base completion. We focus on the family of translational models, whose performance has been lagging.
Kolyvakis, Prodromos +2 more
openaire +1 more source
On Minimizing the Completion Times of Long Flows over Inter-Datacenter WAN
, 2018 Long flows contribute huge volumes of traffic over inter-datacenter WAN. The Flow Completion Time (FCT) is a vital network performance metric that affects the running time of distributed applications and the users' quality of experience.
Noormohammadpour, Mohammad +2 more
core +2 more sources