Results 91 to 100 of about 3,029,250 (288)

Sentiment attribution analysis with hierarchical classification and automatic aspect categorization on online user reviews

, 2022
Due to COVID-19 pandemic, most physical business transactions were pushed online. Online reviews became an excellent source for sentiment analysis to determine a customer\u27s sentiment about a business.
Ravana, Sri Devi, Win, Myat Noe, Shuib, Liyana   +2 more
core   +1 more source

Confidence-guided Prompt Learning for Multimodal Aspect-level Sentiment Analysis [PDF]

Jisuanji kexue
With the increasing volume of data from social media platforms,multimodal aspect-level sentiment analysis is crucial for understanding the underlying emotions of users.Existing research primarily focuses on sentiment analysis tasks by fusing image and ...
LI Maolin, LIN Jiajie, YANG Zhenguo
doaj   +1 more source

Underground Signals: The Ecological Power of Root Volatiles

Advanced Science, EarlyView.
Root volatiles mediate rhizosphere chemical communication, shaping interactions among plants, microbes, herbivores, and natural enemies. Their production, transport, and perception underpin ecological adaptation, multitrophic interactions, and plant resilience, offering opportunities for sustainable crop protection, resilient agroecosystems, and ...
Xueyao Cao, Nanli Song, François Verheggen, Meritxell Pérez‐Hedo, Andrea Clavijo McCormick, Antonino Cusumano, Arthur de Fouchier, Bing Wang, Chen‐Zhu Wang, Emmanuelle Jacquin‐Joly, Gary W. Felton, Geoff M. Gurr, Hao Guo, Jiancai Li, Jin Zhang, Li Chen, Manqun Wang, Michele Ricupero, Peng Han, Peng He, Qi Yan, Qingbo Tang, Qingsong Liu, Shiheng An, Xiangbo Kong, Xiaoling Sun, Xueming Ren, Yuanyuan Song, Yang Liu, Yanhui Guo, Yunhe Li, Xiao Sun   +31 more
wiley   +1 more source

Identifying high-impact sub-structures for convolution kernels in document-level sentiment classification [PDF]

, 2012
Convolution kernels support the modeling of complex syntactic information in machine-learning tasks. However, such models are highly sensitive to the type and size of syntactic structure used.
Shouxun, Lin, Foster, Jennifer, Liu, Qun, He, Yifan, Tu, Zhaopeng, van Genabith, Josef   +5 more
core   +2 more sources

Multitask Learning and BERT Embedding: A Comprehensive Approach to Subjectivity Detection and Aspect-Based Sentiment Analysis

International Journal of Computational Intelligence Systems
The proliferation of online platforms has intensified the need for fine-grained sentiment analysis of customer reviews. While traditional Aspect-based Sentiment Analysis (ABSA) focuses on sentiment classification, it often overlooks the crucial ...
Wing Kin Chong, Hu Ng, Timothy Tzen Vun Yap, Ian K. T. Tan, Vik Tor Goh, Lai Kuan Wong, Dong Theng Cher   +6 more
doaj   +1 more source

Physics‐Constrained Constitutive Learning of Rate‐Limiting Timescales for Efficient Hydrogen‐Based Direct Reduction for Green Steel Making

Advanced Science, EarlyView.
A conversion‐resolved constitutive framework is developed for the hydrogen‐based direct reduction of iron oxide pellets. Effective reaction and transport timescales are inferred directly from measured trajectories and mapped against operating conditions, pellet architecture, and composition. The analysis reveals how late‐stage transport control emerges
Anurag Bajpai, Barak Ratzker, Pasquale Cavaliere, Dierk Raabe   +3 more
wiley   +1 more source

Automated Extraction of Multicomponent Alloy Data Using Large Language Models for Sustainable Design

Advanced Science, EarlyView.
A large language model (LLM) based pipeline is developed to automatically extract a comprehensive and accurate multicomponent alloy database from literature corpus. The extracted dataset is integrated with sustainability indicators to identify potential alloys that outperform existing industrial benchmark materials in terms of both performance and ...
Aravindan Kamatchi Sundaram, Mohit Chakraborty, Sai Mani Kumar Devathi, B. Pabitramohan Prusty, Rohit Batra   +4 more
wiley   +1 more source

AELA-DLSTMs: Attention-enabled and location-aware double LSTMs for aspect-level sentiment classification [PDF]

, 2018
Aspect-level sentiment classification, as a fine-grained task in sentiment classification, aiming to extract sentiment polarity from opinions towards a specific aspect word, has been made tremendous improvements in recent years.
Yang, Qianqian, Shuang, Kai, Ren, Xintao, Li, Rui, Loo, Jonathan   +4 more
core   +1 more source

Voltage‐Reconfigurable Magneto‐Ionic Nanolayers in Dot Arrays for Probabilistic, Materials‐Engineered Security Primitives

Advanced Science, EarlyView.
A magneto‐ionic security‐by‐materials‐design strategy exploits voltage‐driven N3– migration in selectively contacted FeCoN dots, creating reconfigurable sub‐15 nm ferromagnetic sublayers with deterministic and/or probabilistic (single‐domain↔vortex) states, voltage‐tunable probabilities and fully stochastic orientation/chirality.
Irena Spasojevic, Federica Celegato, Alessandro Magni, Paola Tiberto, Jordi Sort   +4 more
wiley   +1 more source

Aspect-based sentiment classification with BERT and AI feedback

Natural Language Processing Journal
Data augmentation has been widely employed in low-resource aspect-based sentiment classification (ABSC) tasks to alleviate the issue of data sparsity and enhance the performance of the model. Unlike previous data augmentation approaches that rely on back translation, synonym replacement, or generative language models such as T5, the generation power of
Lingling Xu, Weiming Wang 0002
openaire   +3 more sources