Lisi Chen
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View article: Co-movement aware trajectory generation via waypoint-guided generative adversarial networks
Co-movement aware trajectory generation via waypoint-guided generative adversarial networks Open
Synthetic trajectory generation is essential for addressing privacy concerns and data scarcity in mobility-related applications. Although existing solutions effectively capture general spatio-temporal features, they often overlook co-movem…
View article: V-VAE: A Variational Auto Encoding Framework Towards Fine-Grained Control over Human-Like Chat
V-VAE: A Variational Auto Encoding Framework Towards Fine-Grained Control over Human-Like Chat Open
With the continued proliferation of Large Language Model (LLM) based chatbots, there is a growing demand for generating responses that are not only linguistically fluent but also consistently aligned with persona-specific traits in convers…
View article: CulFiT: A Fine-grained Cultural-aware LLM Training Paradigm via Multilingual Critique Data Synthesis
CulFiT: A Fine-grained Cultural-aware LLM Training Paradigm via Multilingual Critique Data Synthesis Open
Large Language Models (LLMs) have demonstrated remarkable capabilities across various tasks, yet they often exhibit a specific cultural biases, neglecting the values and linguistic diversity of low-resource regions. This cultural bias not …
View article: RED: Effective Trajectory Representation Learning with Comprehensive Information
RED: Effective Trajectory Representation Learning with Comprehensive Information Open
Trajectory representation learning (TRL) maps trajectories to vectors that can then be used for various downstream tasks, including trajectory similarity computation, trajectory classification, and travel-time estimation. However, existing…
View article: Grid and Road Expressions Are Complementary for Trajectory Representation Learning
Grid and Road Expressions Are Complementary for Trajectory Representation Learning Open
Trajectory representation learning (TRL) maps trajectories to vectors that can be used for many downstream tasks. Existing TRL methods use either grid trajectories, capturing movement in free space, or road trajectories, capturing movement…
View article: Feature Enhanced Spatial–Temporal Trajectory Similarity Computation
Feature Enhanced Spatial–Temporal Trajectory Similarity Computation Open
Trajectory similarity computation is a fundamental function in many applications of urban data analysis, such as trajectory clustering, trajectory compression, and route planning. In this paper, we study trajectory similarity computation o…
View article: DRE: Generating Recommendation Explanations by Aligning Large Language Models at Data-level
DRE: Generating Recommendation Explanations by Aligning Large Language Models at Data-level Open
Recommendation systems play a crucial role in various domains, suggesting items based on user behavior.However, the lack of transparency in presenting recommendations can lead to user confusion. In this paper, we introduce Data-level Recom…
View article: KGTS: Contrastive Trajectory Similarity Learning over Prompt Knowledge Graph Embedding
KGTS: Contrastive Trajectory Similarity Learning over Prompt Knowledge Graph Embedding Open
Trajectory similarity computation serves as a fundamental functionality of various spatial information applications. Although existing deep learning similarity computation methods offer better efficiency and accuracy than non-learning solu…
View article: Personalized Re-ranking for Recommendation with Mask Pretraining
Personalized Re-ranking for Recommendation with Mask Pretraining Open
Re-ranking is to refine the candidate ranking list of recommended items, such that the re-ranked list attracts users to purchase or click more items than the candidate one without re-ranking. Items in the candidate list are often ranked by…
View article: Heterogeneous Region Embedding with Prompt Learning
Heterogeneous Region Embedding with Prompt Learning Open
The prevalence of region-based urban data has opened new possibilities for exploring correlations among regions to improve urban planning and smart-city solutions. Region embedding, which plays a critical role in this endeavor, faces signi…
View article: Next POI Recommendation with Dynamic Graph and Explicit Dependency
Next POI Recommendation with Dynamic Graph and Explicit Dependency Open
Next Point-Of-Interest (POI) recommendation plays an important role in various location-based services. Its main objective is to predict the user's next interested POI based on her previous check-in information. Most existing methods direc…
View article: SSAR-GNN: Self-Supervised Artist Recommendation with Graph Neural Networks
SSAR-GNN: Self-Supervised Artist Recommendation with Graph Neural Networks Open
Artist recommendation plays a vital role in the artist domain. Accurate recommendation can help avoid ineffective searches and acquire comprehensive knowledge regarding relationships among artists. However, existing studies mainly focus on…
View article: Spatial-Temporal Fusion Graph Framework for Trajectory Similarity Computation
Spatial-Temporal Fusion Graph Framework for Trajectory Similarity Computation Open
Trajectory similarity computation is an essential operation in many applications of spatial data analysis. In this paper, we study the problem of trajectory similarity computation over spatial network, where the real distances between obje…
View article: Towards Controlling the Transmission of Diseases: Continuous Exposure Discovery over Massive-Scale Moving Objects
Towards Controlling the Transmission of Diseases: Continuous Exposure Discovery over Massive-Scale Moving Objects Open
Infectious diseases have been recognized as major public health concerns for decades. Close contact discovery is playing an indispensable role in preventing epidemic transmission. In this light, we study the continuous exposure search prob…
View article: Traffic Congestion Alleviation over Dynamic Road Networks: Continuous Optimal Route Combination for Trip Query Streams
Traffic Congestion Alleviation over Dynamic Road Networks: Continuous Optimal Route Combination for Trip Query Streams Open
Route planning and recommendation have attracted much attention for decades. In this paper, we study a continuous optimal route combination problem: Given a dynamic road network and a stream of trip queries, we continuously find an optimal…
View article: Parallel Subtrajectory Alignment over Massive-Scale Trajectory Data
Parallel Subtrajectory Alignment over Massive-Scale Trajectory Data Open
We study the problem of subtrajectory alignment over massive-scale trajectory data. Given a collection of trajectories, a subtrajectory alignment query returns new targeted trajectories by splitting and aligning existing trajectories. The …
View article: Towards Efficient Selection of Activity Trajectories based on Diversity and Coverage
Towards Efficient Selection of Activity Trajectories based on Diversity and Coverage Open
With the prevalence of location based services, activity trajectories are being generated at a rapid pace. The activity trajectory data enriches traditional trajectory data with semantic activities of users, which not only shows where the …
View article: Towards Alleviating Traffic Congestion: Optimal Route Planning for Massive-Scale Trips
Towards Alleviating Traffic Congestion: Optimal Route Planning for Massive-Scale Trips Open
We investigate the problem of optimal route planning for massive-scale trips: Given a traffic-aware road network and a set of trip queries Q, we aim to find a route for each trip such that the global travel time cost for all queries in Q i…
View article: Pay Your Trip for Traffic Congestion: Dynamic Pricing in Traffic-Aware Road Networks
Pay Your Trip for Traffic Congestion: Dynamic Pricing in Traffic-Aware Road Networks Open
Pricing is essential in optimizing transportation resource allocation. Congestion pricing is widely used to reduce urban traffic congestion. We propose and investigate a novel Dynamic Pricing Strategy (DPS) to price travelers' trips in int…
View article: Real-Time Route Search by Locations
Real-Time Route Search by Locations Open
With the proliferation of GPS-based data (e.g., routes and trajectories), it is of great importance to enable the functionality of real-time route search and recommendations. We define and study a novel Continuous Route-Search-by-Location …
View article: Toward Efficient Navigation of Massive-Scale Geo-Textual Streams
Toward Efficient Navigation of Massive-Scale Geo-Textual Streams Open
With the popularization of portable devices, numerous applications continuously produce huge streams of geo-tagged textual data, thus posing challenges to index geo-textual streaming data efficiently, which is an important task in both dat…
View article: Region-Based Message Exploration over Spatio-Temporal Data Streams
Region-Based Message Exploration over Spatio-Temporal Data Streams Open
Massive amount of spatio-temporal data that contain location and text content are being generated by location-based social media. These spatio-temporal messages cover a wide range of topics. It is of great significance to discover local tr…
View article: Distributed Publish/Subscribe Query Processing on the Spatio-Textual Data Stream
Distributed Publish/Subscribe Query Processing on the Spatio-Textual Data Stream Open
Huge amount of data with both space and text information, e.g., geo-tagged tweets, is flooding on the Internet. Such spatio-textual data stream contains valuable information for millions of users with various interests on different keyword…
View article: Distributed Publish/Subscribe Query Processing on the Spatio-Textual Data Stream
Distributed Publish/Subscribe Query Processing on the Spatio-Textual Data Stream Open
Huge amount of data with both space and text information, e.g., geo-tagged tweets, is flooding on the Internet. Such spatio-textual data stream contains valuable information for millions of users with various interests on different keyword…
View article: Towards personalized maps
Towards personalized maps Open
Rich geo-textual data is available online and the data keeps increasing at a high speed. We propose two user behavior models to learn several types of user preferences from geo-textual data, and a prototype system on top of the user pre fe…