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Travel Time Prediction in Real time for GPS Taxi Data Streams and its Applications to Travel Safety
The analysis of data streams offers a great opportunity for development of new methodologies and applications in the area of Intelligent...
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Normalized category travel personality by considering explicit and implicit feedback (NCTP): approach for improving travel recommender systems search result
Large volumes of end-user-generated textual data are assembled every day which leads to the evolution of social media in the form of...
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Scaling law of real traffic jams under varying travel demand
The escalation of urban traffic congestion has reached a critical extent due to rapid urbanization, capturing considerable attention within urban...
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Time Travel Debugging
I think there’s no better quote for a chapter about time travel debuggers than this. A forgettable Shakespeare quote became significant as Huxley...
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Deep intelligent transportation system for travel time estimation on spatio-temporal data
Smart cities can effectively improve urban life quality. But, with the rise in population size, there is an increase in the use of vehicles for...
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Cross Border Travel with Decentralized Identity
The World Economic Forum (WEF) and its partners have joined together under the project name “Sha** the Future of Security in Travel” to address the...
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Travel time prediction based on route links’ similarity
Accurate travel time prediction allows passengers to schedule their journeys efficiently. However, cyclical factors (time intervals of the day,...
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Gct-TTE: graph convolutional transformer for travel time estimation
This paper introduces a new transformer-based model for the problem of travel time estimation. The key feature of the proposed GCT-TTE architecture...
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Hybrid Ensemble-Based Travel Mode Prediction
Travel mode choice (TMC) prediction, which can be formulated as a classification task, helps in understanding what makes citizens choose different...
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ICN: Interactive convolutional network for forecasting travel demand of shared micromobility
Accurate shared micromobility demand predictions are essential for transportation planning and management. Although deep learning methods provide...
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Time Travel and Fail-Safe
Data is an asset that has a major impact on the long-term success of an enterprise. Access to the right data at the right time is extremely important...
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Offline Constrained Backward Time Travel Planning
We model transportation networks as dynamic graphs and introduce the ability for agents to use Backward Time-Travel (BTT) devices at any node to...
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Group recommender systems for tourism: how does personality predict preferences for attractions, travel motivations, preferences and concerns?
To travel in leisure is an emotional experience, and therefore, the more the information about the tourist is known, the more the personalized...
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Investigating the impact of virtual tourism on travel intention during the post-COVID-19 era: evidence from China
This study explores the mechanism that contributes to travel intention in the field of virtual tourism. The overall research method is based on the...
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A negotiation model of individual matching and zonal-based travel behavior in carpooling
Carpooling is a sustainable and ecologically acceptable transportation mode. Individuals commonly engage in coordination and negotiation processes to...
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Combined sentiment score and star rating analysis of travel destination prediction based on user preference using morphological linear neural network model with correlated topic modelling approach
In the context of a globalized world where travel enthusiasts seek personalized recommendations for their favourite destinations, the study delves...
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STTG-TTE: spatial–temporal gated multi-modality approach for travel time estimation based on temporal convolutional networks
Travel time forecasting has become a core component of smart transportation systems, which assists both travelers and traffic organizers with route...
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Collaborative Travel Recommender System Based on Malayalam Travel Reviews
Recommender System is an unsupervised machine learning technique used for users to make decisions on their own choices and interests. Travel and...
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Affective experience in a virtual crowd regulates perceived travel time
Time sometimes feels like it is flying by or slowing down. Previous research indicates objective number of items, subjective affect, and heart rate...
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Construction of Multimodal Dialog System via Knowledge Graph in Travel Domain
When traveling to a foreign city, we often find ourselves in dire need of an intelligent agent that can provide instant and informative responses to...