16 citations · 17 across the 8 of their papers we have counts for
9 papers
Common-Neighbor-Count-Based Representative Possible World Finding on Uncertain Graphs
Chengjie Gu, Xiaoliang Xu, Yuxiang Wang +5
A representative possible world (RPW) is a deterministic graph derived from an uncertain graph where a designated structural feature closely approximates its expected…
Multi-Faceted Continual Knowledge Graph Embedding for Semantic-Aware Link Prediction
Jing Qi, Yuxiang Wang, Zhiyuan Yu +3
Continual Knowledge Graph Embedding (CKGE) aims to continually learn embeddings for new knowledge, i.e., entities and relations, while retaining previously acquired knowledge. Most…
Graph Similarity Computation via Interpretable Neural Node Alignment
Jingjing Wang, Hongjie Zhu, Haoran Xie +3
\Graph similarity computation is an essential task in many real-world graph-related applications such as retrieving the similar drugs given a query chemical compound or finding the…
Graph-guided Cross-composition Feature Disentanglement for Compositional Zero-shot Learning
Yuxia Geng, Runkai Zhu, Jiaoyan Chen +7
Disentanglement of visual features of primitives (i.e., attributes and objects) has shown exceptional results in Compositional Zero-shot Learning (CZSL). However, due to the featur…
Scalable Community Search with Accuracy Guarantee on Attributed Graphs
Yuxiang Wang, Shuzhan Ye, Xiaoliang Xu +4
Given an attributed graph and a query node , \underline{C}ommunity \underline{S}earch over \underline{A}ttributed \underline{G}raphs (CS-AG) aims to find a structure- and at…
Prompting Disentangled Embeddings for Knowledge Graph Completion with Pre-trained Language Model
Yuxia Geng, Jiaoyan Chen, Yuhang Zeng +5
Both graph structures and textual information play a critical role in Knowledge Graph Completion (KGC). With the success of Pre-trained Language Models (PLMs) such as BERT, they ha…
Routing-Guided Learned Product Quantization for Graph-Based Approximate Nearest Neighbor Search
Qiang Yue, Xiaoliang Xu, Yuxiang Wang +2
Given a vector dataset , a query vector , graph-based Approximate Nearest Neighbor Search (ANNS) aims to build a proximity graph (PG) as an index of $\mathc…
DiskANN++: Efficient Page-based Search over Isomorphic Mapped Graph Index using Query-sensitivity Entry Vertex
Jiongkang Ni, Xiaoliang Xu, Yuxiang Wang +4
Given a vector dataset and a query vector , graph-based Approximate Nearest Neighbor Search (ANNS) aims to build a graph index and approximately return…
Random Walk-based Community Key-members Search over Large Graphs
Yuxiang Wang, Yuyang Zhao, Xiaoliang Xu +3
Given a graph , a query node , and an integer , community search (CS) seeks a cohesive subgraph (measured by community models such as -core or -truss) from that…