Bridging odorants and olfactory perception through machine learning: A review

R Zhong, Z Ji, S Wang, H Chen - Trends in Food Science & Technology, 2024 - Elsevier
Background In the field of human olfactory perception (OP) and odorant chemistry (OC), a
substantial corpus of data has been amassed, with efforts directed towards constructing …

MARAN: Supporting awareness of users' routines and preferences for next POI recommendation based on spatial aggregation

X Sun, B Huang, X Wang, D Yu - Expert Systems with Applications, 2024 - Elsevier
Next point-of-interest (POI) recommendation has emerged as an essential task in
recommender systems with the rapid development of location-based social networks …

Utilizing deep learning to explore chemical space for drug lead optimization

R Chakraborty, Y Hasija - Expert Systems with Applications, 2023 - Elsevier
The goal of medicinal chemistry is to improve on existing drug molecules or to create new
ones for use in medicine. This is frequently accomplished by lead optimization, which entails …

Comprehensively assessing priority odorants emitted from swine slurry combining nontarget screening with olfactory threshold prediction

Y Cheng, T Chen, G Zheng, J Yang, B Yu… - Science of The Total …, 2024 - Elsevier
The lack of one-to-one olfactory thresholds (OTs) poses an obstacle to the comprehensive
assessment of priority odorants emitted from swine slurry using mass spectrometric …

ViCGCN: Graph Convolutional Network with Contextualized Language Models for Social Media Mining in Vietnamese

CT Phan, QN Nguyen, CT Dang, TH Do… - arXiv preprint arXiv …, 2023 - arxiv.org
Social media processing is a fundamental task in natural language processing with
numerous applications. As Vietnamese social media and information science have grown …

Graph pooling for graph-level representation learning: a survey

ZP Li, SG Wang, QH Zhang, YJ Pan, NA Xiao… - Artificial Intelligence …, 2024 - Springer
In graph-level representation learning tasks, graph neural networks have received much
attention for their powerful feature learning capabilities. However, with the increasing scales …

EMPPNet: Enhancing Molecular Property Prediction via Cross-modal Information Flow and Hierarchical Attention

Z Zheng, H Wang, Y Tan, C Liang, Y Sun - Expert Systems with Applications, 2023 - Elsevier
Obtaining comprehensive and informative representations of molecules is a crucial
prerequisite for efficient molecule property prediction in artificial intelligence-driven drug …

MolNet_Equi: A Chemically Intuitive, Rotation‐Equivariant Graph Neural Network

J Kim, Y Jeong, WJ Kim, EK Lee… - Chemistry–An Asian …, 2024 - Wiley Online Library
Although deep‐learning (DL) models suggest unprecedented prediction capabilities in
tackling various chemical problems, their demonstrated tasks have so far been limited to the …

机器学习算法在食品气味表征中的应用.

李帅, 柴春祥, 刘建福 - Journal of Chinese Institute of Food …, 2024 - search.ebscohost.com
摘要食品气味的客观表征对于食品生产工艺优化及品质评价具有重要意义, 然而,
食品气味形成机理复杂, 成分繁杂, 加之气味的评价过程易受环境, b 理及感知方式等多种因素的 …

Synergistic Similarity Graph Construction (SSGC) for Steel Plate Fault Diagnosis with Graph Attention Networks

Y Chen, Z Chen, HU Amin - 2023 IEEE 6th International …, 2023 - ieeexplore.ieee.org
Fault diagnosis in industrial production is vital as emerging technologies require innovative
methods to identify subtle fault distinctions. Traditional machine learning approaches for …