Results 51 to 60 of about 31,354 (250)

Advancements in natural language processing: Implications, challenges, and future directions

Telematics and Informatics Reports
This research delves into the latest advancements in Natural Language Processing (NLP) and their broader implications, challenges, and future directions.
Supriyono, Aji Prasetya Wibawa, Suyono, Fachrul Kurniawan   +3 more
doaj   +1 more source

Using Customer Emotional Experience from E-Commerce for Generating Natural Language Evaluation and Advice Reports on Game Products

Journal of ICT Research and Applications, 2019
Investigating customer emotional experience using natural language processing (NLP) is an example of a way to obtain product insight. However, it relies on interpreting and representing the results understandably.
Hamdan Gani, Kiyoshi Tomimatsu
doaj   +1 more source

An Integrated NLP‐ML Framework for Property Prediction and Design of Steels

Advanced Science, EarlyView.
This study presents a data‐driven framework that uses language‐processing techniques to interpret steel processing descriptions and machine‐learning models to predict mechanical properties. By organising complex process histories into meaningful groups and enabling rapid property forecasts, the work supports faster, more informed steel design through ...
Kiran Devraju, Adithya Umanath Rai, Jose Thomson, Marzie Ghorbani, Shujing Zhao, Nick Birbilis   +5 more
wiley   +1 more source

Repérer et caractériser les dynamiques urbaines : l’appui nouveau des humanités numériques

Humanités Numériques
This article presents the work of urban corpus creation and processing, i.e. the methodology adopted, the choices made, the problems encountered and the results obtained at these two stages.
Iris Eshkol-Taravella, Jade Mekki, Olivier Ratouis, Alain Guez, Rémi Simon   +4 more
doaj   +1 more source

CLRe: A Synergistic Dual‐Engine Framework for One‐Step Retrosynthesis Prediction

Advanced Science, EarlyView.
CLRe uses a contrastive difficulty score to order pretrained seq2seq fine‐tuning for retrosynthesis. Reaction embeddings define the ranking score, and a cumulative easy‐to‐hard schedule expands from the easiest subset to the full training set while earlier examples remain active.
Tianhao Su, Xitao Wang, Musen Li, Guanhua Qin, Shunbo Hu, Tong‐Yi Zhang   +5 more
wiley   +1 more source

Quantum Natural Language Processing: A Comprehensive Survey

IEEE Access
By using the quantum mechanics phenomenon, quantum computers provide a new dimension of computational power that drastically accelerates solving complex and resource-intensive problems.
Charles M. Varmantchaonala, Jean Louis K. E. Fendji, Julius Schoning, Marcellin Atemkeng   +3 more
doaj   +1 more source

Editorial for the Special Issue on “Natural Language Processing and Text Mining”

Information, 2019
Natural language processing (NLP) and Text Mining (TM) are a set of overlapping strategies working on unstructured text [...]
Pablo Gamallo, Marcos Garcia
doaj   +1 more source

Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference

Advanced Electronic Materials, EarlyView.
This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho, Dae‐won Kim, Yujin Kim, Jung‐Heum Na, Yuwon Jeong, Dong‐Yeop Lee, Shinhyun Choi   +6 more
wiley   +1 more source

Transfer Learning in Natural Language Processing (NLP)

European Journal of Technology, 2023
Purpose: The purpose of this study is to address the limited use of transfer learning techniques in radio frequency machine learning and to propose a customized taxonomy for radio frequency applications. The aim is to enable performance gains, improved generalization, and cost-effective training data solutions in this specific domain. Methodology: The
openaire   +1 more source

Determinants of Knowledge and Usage of Generative Artificial Intelligence in Agricultural Extension: Evidence From Tennessee Extension Personnel

Agribusiness, EarlyView.
ABSTRACT This paper examines the determinants of generative AI (GenAI) knowledge and usage among agricultural extension professionals. Drawing on survey data from agricultural extension personnel in Tennessee, we employ regression analyses and latent Dirichlet allocation (LDA) for topic modeling of open‐ended responses to study the knowledge and usage ...
Abdelaziz Lawani, Jason de Koff, James Muriuki, Anna‐Liisa Ihuhwa   +3 more
wiley   +1 more source