Federated learning (FL) is an emerging paradigm that enables multiple organizations to
jointly train a model without revealing their private data to each other. This paper studies {\it …

An online ride hailing (ORH) service creates a typical supply-and-demand two-sided market,
which enables riders and drivers to establish optimized rides conveniently via mobile …

In this article, we study the problem of differentially private multi-party data sharing, where
the involved parties assisted by a semi-honest curator collectively generate a shared dataset …

Aggregate nearest neighbor (ANN) query, which can find an optimal location with the
smallest aggregate distance to a group of query users' locations, has received considerable …

Federated learning (FL) has become a prevalent paradigm for training a model
collaboratively on multiple clients with the coordination of a central server. As traditional FL …

The rapidly growing location-based services enable service providers to accumulate
plentiful descriptions on points of interest (POIs), which can be used to support expressive …

Computing Multi-source Shortest Path query with Assembly points () is a fundamental graph
problem. The problem locates a set of assembly points to minimize the overall distance for …

Nowadays, crowdsourcing has witnessed increasing popularity as it can be adopted to solve
many challenging question‐answering tasks. One of the most significant problems in …

Group nearest neighbor (GNN) query enables a group of location‐based service (LBS)
users to retrieve a point from point of interests (POIs) with the minimum aggregate distance …

Online ride-hailing and navigation (ORHN) is a significant application in location-based
services (LBSs). With this application, users can get convenient services in daily travel …