Results 101 to 110 of about 30,602 (303)
Incorporating Literals into Knowledge Graph Embeddings [PDF]
, 2019 Knowledge graphs, on top of entities and their relationships, contain other important elements: literals. Literals encode interesting properties (e.g. the height) of entities that are not captured by links between entities alone. Most of the existing work on embedding (or latent feature) based knowledge graph analysis focuses mainly on the relations ...
Agustinus Kristiadi +4 more
openaire +2 more sources
MADE: Multicurvature Adaptive Embedding for Temporal Knowledge Graph Completion [PDF]
Temporal knowledge graphs (TKGs) are receiving increased attention due to their time-dependent properties and the evolving nature of knowledge over time.
Wang, J +6 more
core +1 more source
What Do Large Language Models Know About Materials?
Advanced Engineering Materials, EarlyView.If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer +2 more
wiley +1 more source
Knowledge Graph Embedding With Interactive Guidance From Entity Descriptions
IEEE Access, 2019 Knowledge Graph (KG) embedding aims to represent both entities and relations into a continuous low-dimensional vector space. Most previous attempts perform the embedding task using only knowledge triples to indicate relations between entities.
Wen'an Zhou, Shirui Wang, Chao Jiang
doaj +1 more source
Advanced Engineering Materials, EarlyView.In this review, the current state of light‐assisted 3D printing as it pertains to engineering musculoskeletal tissues including bone, cartilage, skeletal muscle, tendon, and ligaments is summarized. Common printing techniques, photoreactive materials, and study design choices are compiled and reviewed.
Meagan Morgan, Bin Zhang, Roger Narayan
wiley +1 more source
Embedding Knowledge Graph of Patent Metadata to Measure Knowledge Proximity [PDF]
, 2022 Knowledge proximity refers to the strength of association between any two entities in a structural form that embodies certain aspects of a knowledge base.
Siddharth, L, Li, Guangtong, Luo, Jianxi
core +1 more source
Advanced Engineering Materials, EarlyView.A unified research data management framework for heterogeneous materials data is presented. The system integrates multimodal datasets using ontologies and knowledge graphs, enabling interoperability and FAIR (findable, accessible, interoperable, reusable) data principles. By linking data across scales and workflows, it supports reproducible, Artifitial
Doaa Mohamed +6 more
wiley +1 more source
Fostering Innovation: Streamlining Magnetocaloric Materials Research by Digitalization
Advanced Engineering Materials, EarlyView.Magnetocaloric cooling (MCE) is an environmentally friendly refrigeration method with great potential. Optimizing MCE materials involves the preparation and screening of large quantities of samples, which in turn generates a large amount of data. A digitalization approach is presented that uses ontologies, knowledge graphs, and digital workflows to ...
Simon Bekemeier +17 more
wiley +1 more source
A Hierarchical Knowledge Graph Embedding Framework for Link Prediction
IEEE AccessKnowledge graph embedding maps the semantics of entities and relations to a low-dimensional space by optimizing the vector distance between positive and negative triples.
Shuang Liu +4 more
doaj +1 more source
Knowledge Graph Essentials and Key Technologies
Современные информационные технологии и IT-образование, 2019 In recent decades, the amount of information that humankind has accumulated has increased tremendously. People cannot analyze it effectively using simple algorithms, and data structures due to these approaches do not understand the se¬mantics of the data.
Vladislav Gurin +5 more
doaj +1 more source