Papers point of interests
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Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning
Advances in artificial intelligence (AI) including foundation models (FMs), are increasingly transforming human society, with smart city driving the evolution of urban living.Meanwhile, vehicle crowdsensing (VCS) has eme…
Multi-agent Reinforcement Learningpoint of interestsHGAMN: Heterogeneous Graph Attention Matching Network for Multilingual POI Retrieval at Baidu Maps
The increasing interest in international travel has raised the demand of retrieving point of interests in multiple languages. This is even superior to find local venues such as restaurants and scenic spots in unfamiliar …
Graph Attentionpoint of interestsRetrievalLearning Time Slot Preferences via Mobility Tree for Next POI Recommendation
Next Point-of-Interests (POIs) recommendation task aims to provide a dynamic ranking of POIs based on users' current check-in trajectories. The recommendation performance of this task is contingent upon a comprehensive u…
point of interestsEnhanced Urban Region Profiling with Adversarial Self-Supervised Learning for Robust Forecasting and Security
Urban region profiling plays a crucial role in forecasting and decision-making in the context of dynamic and noisy urban environments. Existing methods often struggle with issues such as noise, data incompleteness, and s…
Adversarial AttackCollaborative FilteringContrastive LearningCrime Prediction+3Smart City Digital Twin Framework for Real-Time Multi-Data Integration and Wide Public Distribution
Digital Twins are digital replica of real entities and are becoming fundamental tools to monitor and control the status of entities, predict their future evolutions, and simulate alternative scenarios to understand the i…
Data Integrationpoint of interestsAttentive Graph Enhanced Region Representation Learning
Representing urban regions accurately and comprehensively is essential for various urban planning and analysis tasks. Recently, with the expansion of the city, modeling long-range spatial dependencies with multiple data …
Graph Attentionpoint of interestsRepresentation LearningDenoising Multi-modal Sequential Recommenders with Contrastive Learning
There is a rapidly-growing research interest in engaging users with multi-modal data for accurate user modeling on recommender systems. Existing multimedia recommenders have achieved substantial improvements by incorpora…
Contrastive LearningDenoisingpoint of interestsRecommendation SystemsAST-GIN: Attribute-Augmented Spatial-Temporal Graph Informer Network for Electric Vehicle Charging Station Availability Forecasting
Electric Vehicle (EV) charging demand and charging station availability forecasting is one of the challenges in the intelligent transportation system. With the accurate EV station situation prediction, suitable charging …
Attributepoint of interestsSelf-supervised Representation Learning for Trip Recommendation
Trip recommendation is a significant and engaging location-based service that can help new tourists make more customized travel plans. It often attempts to suggest a sequence of point of interests (POIs) for a user who r…
Contrastive LearningDiversitypoint of interestsRepresentation LearningSTAN: Spatio-Temporal Attention Network for Next Location Recommendation
The next location recommendation is at the core of various location-based applications. Current state-of-the-art models have attempted to solve spatial sparsity with hierarchical gridding and model temporal relation with…
point of interestsOut-of-Town Recommendation with Travel Intention Modeling
Out-of-town recommendation is designed for those users who leave their home-town areas and visit the areas they have never been to before. It is challenging to recommend Point-of-Interests (POIs) for out-of-town users si…
point of interestsMulti-officer Routing for Patrolling High Risk Areas Jointly Learned from Check-ins, Crime and Incident Response Data
A well-crafted police patrol route design is vital in providing community safety and security in the society. Previous works have largely focused on predicting crime events with historical crime data. The usage of large-…
point of interestsA Survey of Location Prediction on Twitter
Locations, e.g., countries, states, cities, and point-of-interests, are central to news, emergency events, and people's daily lives. Automatic identification of locations associated with or mentioned in documents has bee…
point of interestsPredictionSurvey