Zobrazeno 1 - 10
of 423
pro vyhledávání: '"Sentence Embedding"'
Publikováno v:
Advanced Intelligent Systems, Vol 6, Iss 8, Pp n/a-n/a (2024)
Contrastive learning of sentence representations has achieved great improvements in several natural language processing tasks. However, the supervised contrastive learning model trained on the natural language inference (NLI) dataset is insufficient
Externí odkaz:
https://doaj.org/article/4a8a2f150c634afb931e73a97bc948bf
Publikováno v:
IEEE Access, Vol 12, Pp 159877-159888 (2024)
The latest advancements in unsupervised learning of sentence embeddings predominantly involve employing contrastive learning-based (CL-based) fine-tuning over pre-trained language models. In this study, we analyze the latest sentence embedding method
Externí odkaz:
https://doaj.org/article/ff9de3745a8043e090fcc51665355ebf
Publikováno v:
IEEE Access, Vol 12, Pp 20064-20090 (2024)
Recently, the emergence of social media has opened the way for online harassment in the form of hate speech and offensive language. An automated approach is needed to detect hate and offensive content from social media, which is indispensable. This t
Externí odkaz:
https://doaj.org/article/1f85245548bd4958831f4aeed6ae1e12
Publikováno v:
Applied Sciences, Vol 14, Iss 20, p 9293 (2024)
The perfume industry is a suitable candidate for applying advanced natural language processing techniques, yet most existing studies focus on developing fragrance design systems based on artificial intelligence advances. To meet the increasing demand
Externí odkaz:
https://doaj.org/article/5cd70eaa95f644528c51cb4defcf376c
Publikováno v:
Nongye tushu qingbao xuebao, Vol 35, Iss 8, Pp 88-97 (2023)
[Purpose/Significance] In order to explore the technological gaps in Chinese im-portant agricultural fields and predict the future trends of these gaps, this study investigates technology opportunity discovery in the embryonic and developmental stage
Externí odkaz:
https://doaj.org/article/0b56f003be8f457798540bbac739c03b
Publikováno v:
Plant Methods, Vol 19, Iss 1, Pp 1-16 (2023)
Abstract Background In the era of Agri 4.0 and the popularity of Plantwise systems, the availability of Plant Electronic Medical Records has provided opportunities to extract valuable disease information and treatment knowledge. However, developing a
Externí odkaz:
https://doaj.org/article/f012c7342b21439da1c8ac09fab52812
Publikováno v:
Telematics and Informatics Reports, Vol 13, Iss , Pp 100126- (2024)
Conversations with topics that are locally contextual often produces incoherent topic modeling results using standard methods. Splitting a conversation into its individual utterances makes it possible to avoid this problem. However, with increased da
Externí odkaz:
https://doaj.org/article/28a8b1272d1148d9931ae850cf9461d4
Publikováno v:
Jordanian Journal of Computers and Information Technology, Vol 9, Iss 1, Pp 36-52 (2023)
Text readability is one of the main research areas widely developed in several languages but highly limited when dealing with the Arabic language. The main challenge in this area is to identify an optimal set of features that represent texts and allo
Externí odkaz:
https://doaj.org/article/d49fb84005a843e0b96ffc4d06a9cd33
Autor:
YAO Yi, YANG Fan
Publikováno v:
Jisuanji kexue, Vol 49, Iss 10, Pp 243-251 (2022)
Keywords represent the theme of the text,which is the condensed concept and content of the text.Through keywords,readers can quickly understand the gist and idea of the text and improve the efficiency of information retrieval.In addition,keyword extr
Externí odkaz:
https://doaj.org/article/d361cb33464a4d76b4771c872974db4b
Autor:
Chunchun Wang, Shu Lv
Publikováno v:
Applied Sciences, Vol 14, Iss 7, p 2880 (2024)
This paper presents prefix data augmentation (Prd) as an innovative method for enhancing sentence embedding learning through unsupervised contrastive learning. The framework, dubbed PrdSimCSE, uses Prd to create both positive and negative sample pair
Externí odkaz:
https://doaj.org/article/4e6d10afc3504a42b5eef32b3601898f