VQFT: A Visual Query Approach Based on Full-Text Search for Knowledge Graphs
Summary: VQFT: visual query approach using faceted full-text indexes to let users build knowledge-graph queries via search-engine-like interactions. Integrates a visual constructor and FT→KG translation; demo user studies show improved learnability and usability over existing KG query methods. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Zhaozhuo Li (Tianjin University)
- 2. Xin Wang (Tianjin University)
- 3. Meng Wang (Tongji University)
- 4. Yajun Yang (Tianjin University)
- 5. Bohan Li (Nanjing University)
- 6. Dong Han (Tianjin University)
BibTeX Citation
@article{li_vldb24,
title = {{VQFT: A Visual Query Approach Based on Full-Text Search for Knowledge Graphs}},
author = {Li, Zhaozhuo and Wang, Xin and Wang, Meng and Yang, Yajun and Li, Bohan and Han, Dong},
journal = {PVLDB},
series = {{VLDB} '24},
volume = {17},
number = {12},
pages = {4397--4400},
doi = {10.14778/3685800.3685884},
url = {https://doi.org/10.14778/3685800.3685884},
year = {2024}
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 547 | Cypher: An Evolving Query Language for Property Graphs | 2018 | SIGMOD | 0.00016731552 |
| 13,393 | KGNav: A Knowledge Graph Navigational Visual Query System | 2023 | VLDB | - |
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