KGNav: A Knowledge Graph Navigational Visual Query System
Summary: KGNav: a visual-query system that semi-automatically abstracts a Knowledge Graph Schema by redefining minimal conceptual units via equivalence relations, bridging schema-level global info and instance data. Provides schema-aware operators and an interactive GUI to guide users in constructing deeper queries and reduce tedious low-level exploration. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
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Authors
- 1. Xiang Wang (Tianjin University)
- 2. Xin Wang (Tianjin University)
- 3. Zhaozhuo Li (Tianjin University)
- 4. Dong Han (Tianjin University)
BibTeX Citation
@article{wang_vldb23,
title = {{KGNav: A Knowledge Graph Navigational Visual Query System}},
author = {Wang, Xiang and Wang, Xin and Li, Zhaozhuo and Han, Dong},
journal = {PVLDB},
series = {{VLDB} '23},
volume = {16},
number = {12},
pages = {3946--3949},
doi = {10.14778/3611540.3611592},
url = {https://doi.org/10.14778/3611540.3611592},
year = {2023}
}Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 11,320 | VQFT: A Visual Query Approach Based on Full-Text Search for Knowledge Graphs | 2024 | VLDB | 5.093636e-05 |
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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