Spatial Pattern Matching: A Survey

Schneider, Nicole R.; O'Sullivan, Kent; Samet, Hanan

doi:10.24963/ijcai.2026/889

Spatial Pattern Matching: A Survey

Nicole R. Schneider, Kent O'Sullivan, Hanan Samet

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Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence. Survey Track. Pages 8014-8022.

https://doi.org/10.24963/ijcai.2026/889

Keywords

Data Mining: Information retrieval
Data Mining: Mining spatial and/or temporal data
Knowledge Representation and Reasoning: Qualitative, geometric, spatial, and temporal reasoning
Data Mining: Knowledge graphs and knowledge base completion

Abstract

Recent developments in Artificial Intelligence (AI) have led to new ways for users to search through vast information. However, users may have questions that are grounded in the real world that require spatial inference, for which language models are not well suited. Conversely, traditional spatial search methods, like spatial pattern matching, answer spatial reasoning questions correctly but are noise-intolerant, slow, and brittle. Presently, there are opportunities to integrate AI and spatial pattern matching to enable robust and flexible spatial search. This paper surveys existing spatial pattern matching methods, including the few that apply machine learning to the problem, discussing their efficiency and limitations, and describing opportunities to further enable spatial search through AI.

Nicole R. Schneider, Kent O'Sullivan, and Hanan Samet. 2026. Spatial Pattern Matching: A Survey. In Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence, IJCAI-26. IJCAI, 8014–8022. https://doi.org/10.24963/ijcai.2026/889

@inproceedings{ijcai2026p889,
  title     = {Spatial Pattern Matching: A Survey},
  author    = {Schneider, Nicole R. and O'Sullivan, Kent and Samet, Hanan},
  booktitle = {Proceedings of the Thirty-Fifth International Joint Conference on
               Artificial Intelligence, {IJCAI-26}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {Diego Calvanese},
  pages     = {8014--8022},
  year      = {2026},
  month     = {8},
  note      = {Survey Track},
  doi       = {10.24963/ijcai.2026/889},
  url       = {https://doi.org/10.24963/ijcai.2026/889},
}

TY  - CPAPER
TI  - Spatial Pattern Matching: A Survey
AU  - Schneider, Nicole R.
AU  - O'Sullivan, Kent
AU  - Samet, Hanan
T2  - Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence, IJCAI-26
PB  - International Joint Conferences on Artificial Intelligence Organization
PY  - 2026
SP  - 8014
EP  - 8022
DO  - 10.24963/ijcai.2026/889
UR  - https://doi.org/10.24963/ijcai.2026/889
ER  -