Vertical federated learning is designed to protect user privacy by building local models over
disparate datasets and transferring intermediate parameters without directly revealing the …

In the real world, road networks with weight and label on edges can be applied in several
application domains. The shortest path query with label restrictions has been receiving …

Bipartite graphs are widely used to capture the relationships between two types of entities. In
bipartite graph analysis, finding the maximum balanced biclique (MBB) is an important …

Hypergraphs are a powerful abstraction for modeling high-order relations, which are
ubiquitous in many fields. A hypergraph consists of nodes and hyperedges (ie, subsets of …

Shortest path query on road networks is a fundamental problem to support many location-
based services and wide variant applications. Contraction Hierarchies (CH) is widely …

k-peak is a well-regarded cohesive subgraph model in graph analysis. However, the k-peak
model only considers the direct neighbors of a vertex, consequently limiting its capacity to …

The real-world entities and their relationships can be modeled using temporal graphs,
where each edge is associated with a timestamp denoting the time of interaction between …

Hop-constrained st simple path (HC-st path) enu-meration is a fundamental problem in
graph analysis. Existing solutions for this problem focus on optimizing the processing …

Clique is one of the most fundamental models for cohesive subgraph mining in network
analysis. Existing clique model mainly focuses on unsigned networks. However, in real …

In the real world, road networks with weight and label on edges can be applied in several
application domains. The shortest path query with label restrictions has been receiving …