Results 91 to 100 of about 1,159,266 (295)
, 2020 Word embedding models learn semantically rich vector representations of words and are widely used to initialize natural processing language (NLP) models.
Sonkar, Shashank
core
Using word embedding for bio-event extraction
, 2015 Bio-event extraction is an important phase towards the goal of extracting biological networks from the scientific literature. Recent advances in word embedding make computation of word distribution more ef- ficient and possible.
Li, Chen +11 more
core +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
Misspelling Oblivious Word Embeddings [PDF]
Proceedings of the 2019 Conference of the North, 2019 9 ...
Aleksandra Piktus +5 more
openaire +5 more sources
Advanced Engineering Materials, EarlyView.Reproduction of stacking fault energy calculations from literature with a semi‐automated large language model‐assisted extraction procedure: extraction of simulation protocol, atomistic structures, computational parameters, and reported results, ontology alignment, knowledge graph construction and, finally, recomputation forvalidation.
Sepideh Baghaee Ravari +5 more
wiley +1 more source
Word Embeddings as Statistical Estimators
Sankhya BWord embeddings are a fundamental tool in natural language processing. Currently, word embedding methods are evaluated on the basis of empirical performance on benchmark data sets, and there is a lack of rigorous understanding of their theoretical properties.
Neil Dey +3 more
openaire +4 more sources
Advanced Engineering Materials, EarlyView.Digitalizing electroplating requires both domain knowledge and interoperability. This work introduces PlatOn, a domain ontology for trivalent chromium plating and coating characterization, and a hybrid pipeline that aligns it to a mid‐level reference ontology by combining eight similarity metrics with language model reasoning. Expert‐validated mappings
Janik Harter +10 more
wiley +1 more source
Acronym Disambiguation Using Word Embedding
, 2015 According to the website AcronymFinder.com which is one of the world's largest and most comprehensive dictionaries of acronyms, an average of 37 new human-edited acronym definitions are added every day.
Ji, Lei, Li, Chao, Yan, Jun
core +1 more source
Adaptive Foam 3D Printing of Ultralight and Multifunctional Materials
Advanced Engineering Materials, EarlyView.Adaptive foam 3D printing, enabled by expandable microspheres, imparts cellular structures to thermoplastic and thermosetting polymers, manufactured through a variety of processes including fused filament fabrication, direct ink writing, digital light processing, and inkjet printing.
Nariman Rajabifar, Amir Ameli
wiley +1 more source
Emotional Embeddings: Refining Word Embeddings to Capture Emotional Content of Words
CoRR, 2019 Word embeddings are one of the most useful tools in any modern natural language processing expert's toolkit. They contain various types of information about each word which makes them the best way to represent the terms in any NLP task. But there are some types of information that cannot be learned by these models.
Armin Seyeditabari +3 more
openaire +3 more sources