Xiangyu Ke

Orcid: 0000-0001-8082-7398

Affiliations:
  • Zhejiang University, Hangzhou, China


According to our database1, Xiangyu Ke authored at least 30 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
An Interactive Multi-modal Query Answering System with Retrieval-Augmented Large Language Models.
Proc. VLDB Endow., August, 2024

A Benchmark Study of Deep-RL Methods for Maximum Coverage Problems over Graphs.
Proc. VLDB Endow., July, 2024

Starling: An I/O-Efficient Disk-Resident Graph Index Framework for High-Dimensional Vector Similarity Search on Data Segment.
Proc. ACM Manag. Data, February, 2024

View-based Explanations for Graph Neural Networks.
Proc. ACM Manag. Data, February, 2024

GTS: GPU-based Tree Index for Fast Similarity Search.
Proc. ACM Manag. Data, 2024

Efficient and effective (k, P)-core-based community search over attributed heterogeneous information networks.
Inf. Sci., 2024

User-friendly, Interactive, and Configurable Explanations for Graph Neural Networks with Graph Views.
Proceedings of the Companion of the 2024 International Conference on Management of Data, 2024

Scalable Community Search over Large-scale Graphs based on Graph Transformer.
Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

MUST: An Effective and Scalable Framework for Multimodal Search of Target Modality.
Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

Accelerating Biclique Counting on GPU.
Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

GPU-Accelerated Batch-Dynamic Subgraph Matching.
Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

View-based Explanations for Graph Neural Networks (Extended Abstract).
Proceedings of the 40th International Conference on Data Engineering, ICDE 2024, 2024

Scalable Community Search with Accuracy Guarantee on Attributed Graphs.
Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

2023
Efficient Temporal Butterfly Counting and Enumeration on Temporal Bipartite Graphs.
Proc. VLDB Endow., December, 2023

Efficient and Effective Academic Expert Finding on Heterogeneous Graphs through (<i>k</i>, 𝒫)-Core based Embedding.
ACM Trans. Knowl. Discov. Data, July, 2023

Host Profit Maximization: Leveraging Performance Incentives and User Flexibility.
Proc. VLDB Endow., 2023

Most Probable Densest Subgraphs.
Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

Voting-based Opinion Maximization.
Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

Effective and Efficient Community Search with Graph Embeddings.
Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 2023

2022
Reliability Maximization in Uncertain Graphs.
IEEE Trans. Knowl. Data Eng., 2022

Multi-relation Graph Summarization.
ACM Trans. Knowl. Discov. Data, 2022

Academic Expert Finding via $(k, \mathcal{P})$-Core based Embedding over Heterogeneous Graphs.
Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

2021
Reliability Maximization in Uncertain Graphs (Extended Abstract).
Proceedings of the 37th IEEE International Conference on Data Engineering, 2021

2019
Querying and mining complex graphs : uncertainty and multi-relations
PhD thesis, 2019

An In-Depth Comparison of s-t Reliability Algorithms over Uncertain Graphs.
Proc. VLDB Endow., 2019

Budgeted Reliability Maximization in Uncertain Graphs.
CoRR, 2019

2018
A Demonstration of PERC: Probabilistic Entity Resolution With Crowd Errors.
Proc. VLDB Endow., 2018

Finding Seeds and Relevant Tags Jointly: For Targeted Influence Maximization in Social Networks.
Proceedings of the 2018 International Conference on Management of Data, 2018

2017
Probabilistic Entity Resolution with Imperfect Crowd.
CoRR, 2017

Select Your Questions Wisely: For Entity Resolution With Crowd Errors.
Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017


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