Zobrazeno 1 - 10
of 2 037
pro vyhledávání: '"Language Modeling"'
Autor:
P. Sharmila, Kalaiarasi Sonai Muthu Anbananthen, Deisy Chelliah, S. Parthasarathy, Baarathi Balasubramaniam, Saravanan Nathan Lurudusamy
Publikováno v:
HighTech and Innovation Journal, Vol 5, Iss 3, Pp 627-639 (2024)
Automated subjective assessment presents a significant challenge due to the complex nature of human language and reasoning characterized by semantic variability, subjectivity, language ambiguity, and judgment levels. Unlike objective exams, subjectiv
Externí odkaz:
https://doaj.org/article/aebfc3ac94ea4a02b2075498ee8bdeb0
Autor:
Yasunari Matsuzaka, Ryu Yashiro
Publikováno v:
BioMedInformatics, Vol 4, Iss 3, Pp 1835-1864 (2024)
Human Leukocyte Antigen (HLA) is like a device that monitors the internal environment of the body. T lymphocytes immediately recognize the HLA molecules that are expressed on the surface of the cells of the different individual, attacking it defeats
Externí odkaz:
https://doaj.org/article/0c7ad812977745b7b1735227639ecfee
Autor:
Onur Dogan, Omer Faruk Gurcan
Publikováno v:
Journal of Theoretical and Applied Electronic Commerce Research, Vol 19, Iss 3, Pp 1984-1999 (2024)
E-businesses often face challenges related to customer service and communication, leading to increased dissatisfaction among customers and potential damage to the brand. To address these challenges, data-driven and AI-based approaches have emerged, i
Externí odkaz:
https://doaj.org/article/918b23f64765438f8b6a86562ff94b82
Autor:
Heather Davies, Goran Nenadic, Ghada Alfattni, Mercedes Arguello Casteleiro, Noura Al Moubayed, Sean Farrell, Alan D. Radford, P.-J. M. Noble
Publikováno v:
Frontiers in Veterinary Science, Vol 11 (2024)
In part two of this mini-series, we evaluate the range of machine-learning tools now available for application to veterinary clinical text-mining. These tools will be vital to automate extraction of information from large datasets of veterinary clini
Externí odkaz:
https://doaj.org/article/9cc7f140cf32400ea3ae65442e3e74eb
Autor:
Andrea Busto-Castineira, Francisco Javier Gonzalez-Castano, Silvia Garcia-Mendez, Francisco de Arriba-Perez
Publikováno v:
IEEE Access, Vol 12, Pp 132521-132532 (2024)
In recent years, the field of Natural Language Generation (NLG) has been boosted by the recent advances in deep learning technologies. Nonetheless, these new data-intensive methods introduce language-dependent disparities in NLG as the main training
Externí odkaz:
https://doaj.org/article/4edee7e556f641b8a0b4d02c62c23567
Publikováno v:
IEEE Access, Vol 12, Pp 82057-82067 (2024)
The textual data unlike images, videos, and audio will not get much distorted while transmitting across the network. Steganography is the process of hiding secret data inside innocent data for secured communication. Software-defined radios are promis
Externí odkaz:
https://doaj.org/article/c0307fc7c04d4b4dbe55d0f24f929d4c
Publikováno v:
IEEE Access, Vol 12, Pp 14248-14259 (2024)
In this study, a steganography method based on BERT transformer model is proposed for hiding text data in cover text. The aim is to hide information by replacing specific words within the text using BERT’s masked language modeling (MLM) feature. In
Externí odkaz:
https://doaj.org/article/bf6dd50624b44765a1d534ddb0526317
Publikováno v:
Aerospace, Vol 11, Iss 10, p 813 (2024)
The flight arrival scheduling problem is one of the critical tasks in air traffic operations, aiming to ensure that the flight arrive in the correct sequence safely. Existing methods primarily focus on the terminal area and often overlook the presenc
Externí odkaz:
https://doaj.org/article/d4f88019954947fd99c1b1ed8072cac1
Publikováno v:
EURASIP Journal on Audio, Speech, and Music Processing, Vol 2023, Iss 1, Pp 1-25 (2023)
Abstract This article presents the research work on improving speech recognition systems for the morphologically complex Malayalam language using subword tokens for language modeling. The speech recognition system is built using a deep neural network
Externí odkaz:
https://doaj.org/article/32a243c9f3864e76911eb1639b925d72
Publikováno v:
Journal of Big Data, Vol 10, Iss 1, Pp 1-30 (2023)
Abstract Hypernym discovery is challenging because it aims to find suitable instances for a given hyponym from a predefined hypernym vocabulary. Existing hypernym discovery methods used supervised learning with word embedding from word2vec. However,
Externí odkaz:
https://doaj.org/article/2916b2dd6b0647d894f0e921418d044e