Effectiveness Perspectives and a Deep Relevance Model for Spatial Keyword Queries
Summary: Evaluates spatial keyword queries for geo-textual objects; TkQ merges spatial proximity and text relevance, shown effective. DrW combines neural local-interaction text relevance with a query-dependent balance of proximity, outperforming SOTA. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
No non-self incoming citations found for this paper in this database.
Authors
- 1. Shang Liu (Nanyang Technological University)
- 2. Gao Cong (Nanyang Technological University)
- 3. Kaiyu Feng (Beijing Institute of Technology)
- 4. Wanli Gu (Meituan)
- 5. Fuzheng Zhang (Meituan)
BibTeX Citation
@inproceedings{liu_sigmod23,
title = {{Effectiveness Perspectives and a Deep Relevance Model for Spatial Keyword Queries}},
author = {Liu, Shang and Cong, Gao and Feng, Kaiyu and Gu, Wanli and Zhang, Fuzheng},
series = {{SIGMOD} '23},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3588691},
url = {https://dl.acm.org/doi/10.1145/3588691},
year = {2023}
}Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 7,593 | DEG: Efficient Hybrid Vector Search Using the Dynamic Edge Navigation Graph | 2025 | SIGMOD | 5.4880197e-05 |
| 11,227 | GeoBloom: Revisiting Lightweight Models for Geographic Information Retrieval | 2025 | VLDB | 4.9793485e-05 |
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 9 of 9 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,230 | Efficient Query Processing in Geographic Web Search Engines | 2006 | SIGMOD | 0.00011412036 |
| 1,477 | Efficient Processing of Top-k Spatial Preference Queries | 2011 | VLDB | 0.00010551239 |
| 1,856 | Efficient Retrieval of the Top-k Most Relevant Spatial Web Objects | 2009 | VLDB | 9.4938262e-05 |
| 3,045 | Spatial Keyword Query Processing: An Experimental Evaluation | 2013 | VLDB | 7.72015e-05 |
| 3,528 | Collective Spatial Keyword Queries: A Distance Owner-Driven Approach | 2013 | SIGMOD | 7.2303439e-05 |
| 4,255 | Retrieving Top-k Prestige-Based Relevant Spatial Web Objects | 2010 | VLDB | 6.7010852e-05 |
| 4,574 | Collective Spatial Keyword Querying | 2011 | SIGMOD | 6.5257688e-05 |
| 4,797 | Reverse Spatial and Textual k Nearest Neighbor Search | 2011 | SIGMOD | 6.4113285e-05 |
| 9,688 | Points-of-Interest Relationship Inference with Spatial-enriched Graph Neural Networks | 2022 | VLDB | 5.1408423e-05 |
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 11,983 | Proportionality in Spatial Keyword Search | 2021 | SIGMOD |
| 2 | 1,230 | Efficient Query Processing in Geographic Web Search Engines | 2006 | SIGMOD |
| 3 | 4,797 | Reverse Spatial and Textual k Nearest Neighbor Search | 2011 | SIGMOD |
| 4 | 4,574 | Collective Spatial Keyword Querying | 2011 | SIGMOD |
| 5 | 8,991 | Querying Geo-Textual Data: Spatial Keyword Queries and Beyond | 2016 | SIGMOD |
| 6 | 6,346 | Clue-based Spatio-textual Query | 2017 | VLDB |
| 7 | 10,247 | Top-k Relevant Semantic Place Retrieval on Spatial RDF Data | 2016 | SIGMOD |
| 8 | 3,045 | Spatial Keyword Query Processing: An Experimental Evaluation | 2013 | VLDB |
| 9 | 4,255 | Retrieving Top-k Prestige-Based Relevant Spatial Web Objects | 2010 | VLDB |
| 10 | 1,856 | Efficient Retrieval of the Top-k Most Relevant Spatial Web Objects | 2009 | VLDB |