AIMC Topic: Travel

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Enhanced sentiment analysis in tourism reviews via multimodal graph convolutional networks.

PloS one
In recent years, multimodal sentiment analysis has gained prominence due to its ability to leverage diverse data types for improved accuracy. However, combining text and image modalities presents challenges in effectively integrating and processing t...

MONTUR project: Dataset for understanding and forecasting tourist flows.

PloS one
This study presents an advanced system for monitoring and forecasting tourist flows in the Aosta Valley using distributed sensor technologies, cameras, and machine learning algorithms. This innovative system is designed to provide real-time data on a...

MTSA-SC: A multi-task learning approach for individual trip destination prediction with multi-trajectory subsequence alignment and space-aware loss functions.

PloS one
Individual Trip Destination Prediction aims to accurately forecast an individual's future travel destinations by analyzing their historical trajectory data, holding significant application value in intelligent navigation, personalized recommendations...

Enhancing happiness and well-being: AI-driven solutions for accessible, inclusive travel experiences for people with disabilities.

Disability and rehabilitation. Assistive technology
PURPOSE: This study explores the relationship between happiness and well-being, with a particular focus on how Artificial Intelligence (AI) serves as a catalyst for enhancing the quality of life of individuals with disabilities. The research aims to ...

Point-of-interest recommender model using geo-tagged photos in accordance with imperialist Fuzzy C-means clustering.

PloS one
Although recommender systems (RSs) strive to provide recommendations based on individuals' histories and preferences, most recommendations made by these systems do not utilize location and time-based information. This paper presents a travel recommen...

Machine learning analysis of the effects of COVID-19 on migration patterns.

Scientific reports
This study investigates the impact of the COVID-19 pandemic on European tourist mobility patterns from 2019 to 2021 by conceptualizing countries as monomers emitting radiation to model and analyze their patterns through the lens of socio-economics an...

Gender disparities in rural motorcycle accidents: A neural network analysis of travel behavior impact.

Accident; analysis and prevention
Rural road accidents involving motorcycle riders present a formidable challenge to road safety globally. This study offers a comprehensive gender-based comparative analysis of rural road accidents among motorcycle riders, aimed at illuminating factor...

Construction of an aerolysin-based multi-epitope vaccine against an machine learning and artificial intelligence-supported approach.

Frontiers in immunology
, a gram-negative coccobacillus bacterium, can cause various infections in humans, including septic arthritis, diarrhea (traveler's diarrhea), gastroenteritis, skin and wound infections, meningitis, fulminating septicemia, enterocolitis, peritonitis,...

A new era is emerging at scientific user facilities.

IUCrJ
Global scientific exchange has been profoundly perturbed by the COVID-19 pandemic, altering user travel behaviours and accelerating the use of remote access. Combined with the advent of artificial intelligence (AI), these trends together can change h...

Deep learning hybrid model for analyzing and predicting the impact of imported malaria cases from Africa on the rise of Plasmodium falciparum in China before and during the COVID-19 pandemic.

PloS one
BACKGROUND: Plasmodium falciparum cases are rising in China due to the imported malaria cases from African countries. The main goal of this study is to examine the impact of imported malaria cases in African countries on the rise of P. falciparum cas...