42 citations · 62 across the 34 of their papers we have counts for
36 papers
HYDRA: Proactive Android Malware Drift Adaptation via Hierarchical Graph Contrastive Learning
Han Chen, Hanchen Wang, Hongmei Chen +3
Concept drift, driven by the rapid evolution of Android malware, severely degrades the performance of machine learning detectors. Current adaptation strategies are often reactive,…
Algebraic Subgraph Counting
Qiuyu Guo, Jianye Yang, Wenjie Zhang +3
Subgraph isomorphism counting is a fundamental problem in graph analytics, which aims to find the number of subgraph isomorphisms of a query graph in a data graph. The candidate tr…
Efficient Approximate Nearest Neighbor Search under Multi-Attribute Range Filter
Yuanhang Yu, Dawei Cheng, Ying Zhang +3
Nearest neighbor search on high-dimensional vectors is fundamental in modern AI and database systems. In many real-world applications, queries involve constraints on multiple numer…
RLMiner: Finding the Most Frequent k-sized Subgraph via Reinforcement Learning
Wei Huang, Hanchen Wang, Dong Wen +4
Identifying the most frequent induced subgraph of size in a target graph is a fundamental graph mining problem with direct implications for Web-related data mining and social n…
HyperJoin: LLM-augmented Hypergraph Link Prediction for Joinable Table Discovery
Shiyuan Liu, Jianwei Wang, Xuemin Lin +3
As a pivotal task in data lake management, joinable table discovery has attracted widespread interest. While existing language model-based methods achieve remarkable performance by…
UniCom: Towards a Unified and Cohesiveness-aware Framework for Community Search and Detection
Yifan Zhu, Hanchen Wang, Wenjie Zhang +2
Searching and detecting communities in real-world graphs underpins a wide range of applications. Despite the success achieved, current learning-based solutions regard community sea…
FADTI: Fourier and Attention Driven Diffusion for Multivariate Time Series Imputation
Runze Li, Hanchen Wang, Wenjie Zhang +4
Multivariate time series imputation is fundamental in applications such as healthcare, traffic forecasting, and biological modeling, where sensor failures and irregular sampling le…
DHG-Bench: A Comprehensive Benchmark for Deep Hypergraph Learning
Fan Li, Xiaoyang Wang, Wenjie Zhang +2
Deep graph models have achieved great success in network representation learning. However, their focus on pairwise relationships restricts their ability to learn pervasive higher-o…
HiGraph: A Large-Scale Hierarchical Graph Dataset for Malware Analysis
Han Chen, Hanchen Wang, Hongmei Chen +3
The advancement of graph-based malware analysis is critically limited by the absence of large-scale datasets that capture the inherent hierarchical structure of software. Existing…
Triangle Counting in Hypergraph Streams: A Complete and Practical Approach
Lingkai Meng, Long Yuan, Xuemin Lin +2
Triangle counting in hypergraph streams, including both hyper-vertex and hyper-edge triangles, is a fundamental problem in hypergraph analytics, with broad applications. However, e…
Accelerating Historical K-Core Search in Temporal Graphs
Zhuo Ma, Dong Wen, Kaiyu Chen +3
We study the temporal k-core component search (TCCS), which outputs the k-core containing the query vertex in the snapshot over an arbitrary query time window in a temporal graph.…
Accelerating K-Core Computation in Temporal Graphs
Zhuo Ma, Dong Wen, Hanchen Wang +3
We address the problem of enumerating all temporal k-cores given a query time range and a temporal graph, which suffers from poor efficiency and scalability in the state-of-the-art…
WOCD: A Semi-Supervised Method for Overlapping Community Detection Using Weak Cliques
Shaozhen Ma, Hanchen Wang, Dong Wen +3
Overlapping community detection (OCD) is a fundamental graph data analysis task for extracting graph patterns. Traditional OCD methods can be broadly divided into node clustering a…
Motif Counting in Complex Networks: A Comprehensive Survey
Haozhe Yin, Kai Wang, Wenjie Zhang +3
Motif counting plays a crucial role in understanding the structural properties of networks. By computing motif frequencies, researchers can draw key insights into the structural pr…
DiffGED: Computing Graph Edit Distance via Diffusion-based Graph Matching
Wei Huang, Hanchen Wang, Dong Wen +3
The Graph Edit Distance (GED) problem, which aims to compute the minimum number of edit operations required to transform one graph into another, is a fundamental challenge in graph…
UniDyG: A Unified and Effective Representation Learning Approach for Large Dynamic Graphs
Yuanyuan Xu, Wenjie Zhang, Xuemin Lin +1
Dynamic graphs are formulated in continuous-time or discrete-time dynamic graphs. They differ in temporal granularity: Continuous-Time Dynamic Graphs (CTDGs) exhibit rapid, localiz…
AI-Empowered Catalyst Discovery: A Survey from Classical Machine Learning Approaches to Large Language Models
Yuanyuan Xu, Hanchen Wang, Wenjie Zhang +6
Catalysts are essential for accelerating chemical reactions and enhancing selectivity, which is crucial for the sustainable production of energy, materials, and bioactive compounds…
Unlocking Multi-Modal Potentials for Link Prediction on Dynamic Text-Attributed Graphs
Yuanyuan Xu, Wenjie Zhang, Ying Zhang +2
Dynamic Text-Attributed Graphs (DyTAGs) are a novel graph paradigm that captures evolving temporal events (edges) alongside rich textual attributes. Existing studies can be broadly…
Ensemble-based Deep Multilayer Community Search
Jianwei Wang, Yuehai Wang, Kai Wang +3
Multilayer graphs, consisting of multiple interconnected layers, are widely used to model diverse relationships in the real world. A community is a cohesive subgraph that offers va…
On LLM-Enhanced Mixed-Type Data Imputation with High-Order Message Passing
Jianwei Wang, Kai Wang, Ying Zhang +3
Missing data imputation, which aims to impute the missing values in the raw datasets to achieve the completeness of datasets, is crucial for modern data-driven models like large la…
Efficient Unsupervised Community Search with Pre-trained Graph Transformer
Jianwei Wang, Kai Wang, Xuemin Lin +2
Community search has aroused widespread interest in the past decades. Among existing solutions, the learning-based models exhibit outstanding performance in terms of accuracy by le…
Neural Attributed Community Search at Billion Scale
Jianwei Wang, Kai Wang, Xuemin Lin +2
Community search has been extensively studied in the past decades. In recent years, there is a growing interest in attributed community search that aims to identify a community bas…
Batch Hop-Constrained s-t Simple Path Query Processing in Large Graphs
Long Yuan, Kongzhang Hao, Xuemin Lin +1
Hop-constrained s-t simple path (HC-s-t path) enumeration is a fundamental problem in graph analysis. Existing solutions for this problem focus on optimizing the processing perform…
High-Ratio Compression for Machine-Generated Data
Jiujing Zhang, Zhitao Shen, Shiyu Yang +7
Machine-generated data is rapidly growing and poses challenges for data-intensive systems, especially as the growth of data outpaces the growth of storage space. To cope with the s…