Reinforcement Learning Based Query Vertex Ordering Model for Subgraph Matching

no code implementations • 25 Jan 2022 • Hanchen Wang, Ying Zhang, Lu Qin, Wei Wang, Wenjie Zhang, Xuemin Lin

In recent years, many advanced techniques for query vertex ordering (i. e., matching order generation) have been proposed to reduce the unpromising intermediate results according to the preset heuristic rules.

reinforcement-learning Reinforcement Learning (RL)

On Random Walk Based Graph Sampling

1 code implementation • ‏‏‎ ‎ 2020 • Rong-Hua Li, Jeffrey Xu Yu, Lu Qin, Rui Mao, Tan Ji

In this paper, we first present a comprehensive analysis of the drawbacks of three widely-used random walk based graph sampling algorithms, called re-weighted random walk (RW) algorithm, Metropolis-Hastings random walk (MH) algorithm and maximum-degree random walk (MD) algorithm.

Graph Sampling

GoGNN: Graph of Graphs Neural Network for Predicting Structured Entity Interactions

1 code implementation • 12 May 2020 • Hanchen Wang, Defu Lian, Ying Zhang, Lu Qin, Xuemin Lin

We observe that existing works on structured entity interaction prediction cannot properly exploit the unique graph of graphs model.

Taming the Expressiveness and Programmability of Graph Analytical Queries

no code implementations • 20 Apr 2020 • Lu Qin, Longbin Lai, Kongzhang Hao, Zhongxin Zhou, Yiwei Zhao, Yuxing Han, Xuemin Lin, Zhengping Qian, Jingren Zhou

Graph database has enjoyed a boom in the last decade, and graph queries accordingly gain a lot of attentions from both the academia and industry.

Code Generation

Binarized Graph Neural Network

no code implementations • 19 Apr 2020 • Hanchen Wang, Defu Lian, Ying Zhang, Lu Qin, Xiangjian He, Yiguang Lin, Xuemin Lin

Our proposed method can be seamlessly integrated into the existing GNN-based embedding approaches to binarize the model parameters and learn the compact embedding.

Graph Embedding

A Survey and Experimental Analysis of Distributed Subgraph Matching

1 code implementation • 27 Jun 2019 • Longbin Lai, Zhu Qing, Zhengyi Yang, Xin Jin, Zhengmin Lai, Ran Wang, Kongzhang Hao, Xuemin Lin, Lu Qin, Wenjie Zhang, Ying Zhang, Zhengping Qian, Jingren Zhou

We conduct extensive experiments for both unlabelled matching and labelled matching to analyze the performance of distributed subgraph matching under various settings, which is finally summarized as a practical guide.

Databases

Efficient Graph Edit Distance Computation and Verification via Anchor-aware Lower Bound Estimation

no code implementations • 20 Sep 2017 • Lijun Chang, Xing Feng, Xuemin Lin, Lu Qin, Wenjie Zhang

Graph edit distance (GED) is an important similarity measure adopted in a similarity-based analysis between two graphs, and computing GED is a primitive operator in graph database analysis.

Databases Data Structures and Algorithms

Emotion Corpus Construction Based on Selection from Hashtags

no code implementations • LREC 2016 • Minglei Li, Yunfei Long, Lu Qin, Wenjie Li

Secondly, a SVM based classifier is used to select the data whose natural labels are consistent with the predicted labels.

Emotion Classification