16 citations · 23 across the 11 of their papers we have counts for
14 papers
Interpretable Unsupervised Community Detection with LLM-Symbolized Structured Processes
Aoting Zeng, Kai Wang, Jianwei Wang +3
Community detection is a fundamental task in graph analytics that aims to identify cohesive groups of entities with similar behaviors or interests. Classic objective-driven methods…
Empowering Tabular Data Preparation with Language Models: Why and How?
Mengshi Chen, Yuxiang Sun, Tengchao Li +5
Data preparation is a critical step in enhancing the usability of tabular data and thus boosts downstream data-driven tasks. Traditional methods often face challenges in capturing…
HiTeC: Hierarchical Contrastive Learning on Text-Attributed Hypergraph with Semantic-Aware Augmentation
Mengting Pan, Fan Li, Chen Chen +2
Contrastive learning (CL) has become a dominant paradigm for self-supervised hypergraph learning, enabling effective training without costly labels. However, node entities in real-…
LogLite: Lightweight Plug-and-Play Streaming Log Compression
Benzhao Tang, Shiyu Yang, Zhitao Shen +3
Log data is a vital resource for capturing system events and states. With the increasing complexity and widespread adoption ofmodern software systems and IoT devices, the daily vol…
Towards Unsupervised Training of Matching-based Graph Edit Distance Solver via Preference-aware GAN
Wei Huang, Hanchen Wang, Dong Wen +3
Graph Edit Distance (GED) is a fundamental graph similarity metric widely used in various applications. However, computing GED is an NP-hard problem. Recent state-of-the-art hybrid…
OSS-UAgent: An Agent-based Usability Evaluation Framework for Open Source Software
Lingkai Meng, Yu Shao, Long Yuan +6
Usability evaluation is critical to the impact and adoption of open source software (OSS), yet traditional methods relying on human evaluators suffer from high costs and limited sc…
Efficient Computation of Hyper-triangles on Hypergraphs
Haozhe Yin, Kai Wang, Wenjie Zhang +3
Hypergraphs, which use hyperedges to capture groupwise interactions among different entities, have gained increasing attention recently for their versatility in effectively modelin…
ProbDiffFlow: An Efficient Learning-Free Framework for Probabilistic Single-Image Optical Flow Estimation
Mo Zhou, Jianwei Wang, Xuanmeng Zhang +5
This paper studies optical flow estimation, a critical task in motion analysis with applications in autonomous navigation, action recognition, and film production. Traditional opti…
Counting Butterflies over Streaming Bipartite Graphs with Duplicate Edges
Lingkai Meng, Long Yuan, Xuemin Lin +3
Bipartite graphs are commonly used to model relationships between two distinct entities in real-world applications, such as user-product interactions, user-movie ratings and collab…
Simpler is More: Efficient Top-K Nearest Neighbors Search on Large Road Networks
Yiqi Wang, Long Yuan, Wenjie Zhang +3
Top-k Nearest Neighbors (kNN) problem on road network has numerous applications on location-based services. As direct search using the Dijkstra's algorithm results in a large searc…
A Survey of Distributed Graph Algorithms on Massive Graphs
Lingkai Meng, Yu Shao, Long Yuan +7
Distributed processing of large-scale graph data has many practical applications and has been widely studied. In recent years, a lot of distributed graph processing frameworks and…
Efficient Non-Learning Similar Subtrajectory Search
Jiabao Jin, Peng Cheng, Lei Chen +2
Similar subtrajectory search is a finer-grained operator that can better capture the similarities between one query trajectory and a portion of a data trajectory than the tradition…
Dynamic Private Task Assignment under Differential Privacy
Leilei Du, Peng Cheng, Libin Zheng +4
Data collection is indispensable for spatial crowdsourcing services, such as resource allocation, policymaking, and scientific explorations. However, privacy issues make it challen…
Online Ridesharing with Meeting Points [Technical Report]
Jiachuan Wang, Peng Cheng, Libin Zheng +2
Nowadays, ridesharing becomes a popular commuting mode. Dynamically arriving riders post their origins and destinations, then the platform assigns drivers to serve them. In ridesha…