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Documents authored by Cavazzi, Stefano

Document
DOI: 10.4230/LIPIcs.COSIT.2026.10
Much of Geospatial Web Search Is Beyond Traditional GIS

Authors: Ilya Ilyankou, Stefano Cavazzi, and James Haworth

Published in: LIPIcs, Volume 393, 17th International Conference on Spatial Information Theory (COSIT 2026)

Abstract
Web search queries concern place far more often than existing labelling schemes suggest, yet the landscape of geospatial web search queries - what people ask of place, and how often - remains poorly characterised at scale. We apply dense sentence embeddings, a lightweight SetFit classifier, and density-based clustering to the full MS MARCO corpus of 1.01 million real Bing queries without prior filtering for toponyms or spatial keywords, identifying 181,827 geospatial queries (18.0%), nearly threefold the 6.17% labelled as Location in the original annotations. The resulting taxonomy of 88 query categories reveals that geospatial web search is dominated by transactional and practical lookups: costs and prices alone account for 15.3% of geospatial queries, nearly twice the size of the entire physical geography theme. Much of this activity - costs, opening hours, contact details, weather, travel recommendations - falls outside the scope of what traditional GIS and knowledge graphs are built to serve. The categories vary substantially in the kind of answer they admit, from deterministic lookups answerable from spatial databases or knowledge graphs to evaluative or temporally volatile queries that require generative or real-time systems. We discuss implications for hybrid retrieval architectures and for benchmarks of geographic reasoning in large language models. We openly release the labelled dataset, classifier, and taxonomy.
Cite as

Ilya Ilyankou, Stefano Cavazzi, and James Haworth. Much of Geospatial Web Search Is Beyond Traditional GIS. In 17th International Conference on Spatial Information Theory (COSIT 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 393, pp. 10:1-10:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{ilyankou_et_al:LIPIcs.COSIT.2026.10,
  author =	{Ilyankou, Ilya and Cavazzi, Stefano and Haworth, James},
  title =	{{Much of Geospatial Web Search Is Beyond Traditional GIS}},
  booktitle =	{17th International Conference on Spatial Information Theory (COSIT 2026)},
  pages =	{10:1--10:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-438-3},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{393},
  editor =	{Timpf, Sabine and Filomena, Gabriele and Kapaj, Armand and Zhu, Rui and Giudice, Nicholas A. and Manley, Ed},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2026.10},
  URN =		{urn:nbn:de:0030-drops-275546},
  doi =		{10.4230/LIPIcs.COSIT.2026.10},
  annote =	{Keywords: Web search queries, geographic information retrieval, query classification, geospatial query taxonomy, MS MARCO, sentence embeddings, density-based clustering, GeoAI, large language models, place theory}
}
Document
Short Paper
DOI: 10.4230/LIPIcs.GIScience.2023.15
Why Is Greenwich so Common? Quantifying the Uniqueness of Multivariate Observations (Short Paper)

Authors: Andrea Ballatore and Stefano Cavazzi

Published in: LIPIcs, Volume 277, 12th International Conference on Geographic Information Science (GIScience 2023)

Abstract
The concept of uniqueness can play an important role when the assessment of an observation’s distinctiveness is essential. This article introduces a distance-based uniqueness measure that quantifies the relative rarity or commonness of a multi-variate observation within a dataset. Unique observations exhibit rare combinations of values, and not necessarily extreme values. Taking a cognitive psychological perspective, our measure defines uniqueness as the sum of distances between a target observation and all other observations. After presenting the measure u and its corresponding standardised version u_z, we propose a method to calculate a p value through a probability density function. We then demonstrate the measure’s behaviour in a case study on the uniqueness of Greater London boroughs, based on real-world socioeconomic variables. This initial investigation indicates that u can support exploratory data analysis.
Cite as

Andrea Ballatore and Stefano Cavazzi. Why Is Greenwich so Common? Quantifying the Uniqueness of Multivariate Observations (Short Paper). In 12th International Conference on Geographic Information Science (GIScience 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 277, pp. 15:1-15:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{ballatore_et_al:LIPIcs.GIScience.2023.15,
  author =	{Ballatore, Andrea and Cavazzi, Stefano},
  title =	{{Why Is Greenwich so Common? Quantifying the Uniqueness of Multivariate Observations}},
  booktitle =	{12th International Conference on Geographic Information Science (GIScience 2023)},
  pages =	{15:1--15:6},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-288-4},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{277},
  editor =	{Beecham, Roger and Long, Jed A. and Smith, Dianna and Zhao, Qunshan and Wise, Sarah},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2023.15},
  URN =		{urn:nbn:de:0030-drops-189109},
  doi =		{10.4230/LIPIcs.GIScience.2023.15},
  annote =	{Keywords: uniqueness, distinctiveness, similarity, outlier detection, multivariate data}
}

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