Results 71 to 80 of about 24,198 (261)
Deconstructing Word Embeddings
CoRR, 2019 A review of Word Embedding Models through a deconstructive approach reveals their several shortcomings and inconsistencies. These include instability of the vector representations, a distorted analogical reasoning, geometric incompatibility with linguistic features, and the inconsistencies in the corpus data.
openaire +2 more sources
All Word Embeddings from One Embedding
CoRR, 2020 NeurIPS ...
Sho Takase, Sosuke Kobayashi
openaire +3 more sources
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
A triple joint extraction method combining hybrid embedding and relational label embedding
Dianxin kexue, 2023 The purpose of triple extraction is to obtain relationships between entities from unstructured text and apply them to downstream tasks.The embedding mechanism has a great impact on the performance of the triple extraction model, and the embedding vector ...
Jianfeng DAI +3 more
doaj +2 more sources
Sentiment-Aware Word Embedding for Emotion Classification
Applied Sciences, 2019 Word embeddings are effective intermediate representations for capturing semantic regularities between words in natural language processing (NLP) tasks. We propose sentiment-aware word embedding for emotional classification, which consists of integrating
Xingliang Mao +4 more
doaj +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
Refining electronic medical records representation in manifold subspace
BMC Bioinformatics, 2022 Background Electronic medical records (EMR) contain detailed information about patient health. Developing an effective representation model is of great significance for the downstream applications of EMR.
Bolin Wang +5 more
doaj +1 more source
Advanced Engineering Materials, EarlyView.Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch +3 more
wiley +1 more source
New method of text representation model based on neural network
Tongxin xuebao, 2017 Method of text representation model was proposed to extract word-embedding from text feature.Firstly,the word-embedding of the dual word-embedding list based on dictionary index and the corresponding part of speech index was created.Then,feature vectors ...
Shui-fei ZENG +3 more
doaj +2 more sources