The development of correct and efficient software can be hindered by
com...
Emerging tools bring forth fresh approaches to work, and the field of na...
Similar subtrajectory search is a finer-grained operator that can better...
The widespread use of graph data in various applications and the highly
...
Logical query answering over Knowledge Graphs (KGs) is a fundamental yet...
The amount of data has growing significance in exploring cutting-edge
ma...
Spatial objects often come with textual information, such as Points of
I...
Information cascade in online social networks can be rather negative, e....
Data collection is indispensable for spatial crowdsourcing services, suc...
Recently, prompt-based learning has become a very popular solution in ma...
The shortest-path distance is a fundamental concept in graph analytics a...
Nowadays, ridesharing becomes a popular commuting mode. Dynamically arri...
The Feedback vertex set with the minimum size is one of Karp's 21 NP-com...
Network alignment task, which aims to identify corresponding nodes in
di...
Heterogeneous graphs, which contain nodes and edges of multiple types, a...
The capability of generating speech with specific type of emotion is des...
Clique is one of the most fundamental models for cohesive subgraph minin...
Listing all k-cliques is a fundamental problem in graph mining, with
app...
Subgraph matching is a fundamental problem in various fields that use gr...
With the development of traffic prediction technology, spatiotemporal
pr...
The engagement of each user in a social network is an essential indicato...
Community detection, aiming to group the graph nodes into clusters with ...
Code generation is crucial to reduce manual software development efforts...
Automatic software development has been a research hot spot in the field...
Recent advances in reinforcement learning have inspired increasing inter...
Existing graph neural networks (GNNs) largely rely on node embeddings, w...
Graph plays a vital role in representing entities and their relationship...
Bipartite graphs are widely used to model relationships between two type...
We propose a novel cohesive subgraph model called τ-strengthened
(α,β)-c...
Matrix Factorization (MF) has been widely applied in machine learning an...
Triangle listing is an important topic significant in many practical
app...
Interactive recommendation aims to learn from dynamic interactions betwe...
The boolean satisfiability problem is a famous NP-complete problem in
co...
Cohesive subgraph mining in bipartite graphs becomes a popular research ...
Generalized zero-shot learning (GZSL) tackles the problem of learning to...
Recently there emerge many distributed algorithms that aim at solving
su...
A popular model to measure the stability of a network is k-core - the ma...
With the rapid development of information technologies, various big grap...
Driven by many real applications, we study the problem of seeded graph
m...
In this paper, we study the problem of approximate containment similarit...
Driven by deep neural networks and large scale datasets, scene text dete...
Electroencephalography (EEG) signals reflect activities on certain brain...
Community search over large graphs is a fundamental problem in graph
ana...
In this article, we study the efficient dynamical computation of all-pai...
Graph edit distance (GED) is an important similarity measure adopted in ...
Given a query photo issued by a user (q-user), the landmark retrieval is...
Multi-view spectral clustering, which aims at yielding an agreement or
c...