Presentation – Platial Analysis Lab

Two presentations at TRB2024

November 1, 2023

Two doctoral students from the lab will attend and present at the 103rd Annual Meeting of the Transportation Research Board…

New “critical toponomy” paper at EMNLP

October 25, 2023

In a new paper accepted at EMNLP 2023, we introduce the concept of “critical toponymy” as an underexplored theoretical framework in applied natural language processing…

Best paper award at GIScience ’23

October 6, 2023

Our paper “Platial k-anonymity” was selected for the Best Full Paper award at this year’s GIScience conference…

Platial Lab at UCGIS Symposium

June 7, 2023

This week Prof. McKenzie was a panellist at the 2023 University Consortium for Geographic Information Science (UCGIS) symposium at Yale University…

Platial Lab at AAG 2023

April 4, 2023

Two members of the lab attended the American Association of Geographers annual meeting in Denver, CO this year…

Two papers in upcoming symposia

November 30, 2021

Papers published by lab members were recently accepted into two upcoming symposia this December…

IJGIS GeoAI Editorial Webinar

February 2, 2021

Professor McKenzie will join coauthors to present their editorial GeoAI: spatially explicit artificial intelligence techniques for geographic knowledge discovery and beyond…

Brunila, Mikael; LaViolette, Jack; CH-Wang, Sky; Verma, Priyanka; Féré, Clara; McKenzie, Grant

Toward a Critical Toponymy Framework for Named Entity Recognition: A Case Study of Airbnb in New York City Proceedings Article Forthcoming

In: Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP2023), Forthcoming.

Abstract | Links | BibTeX

McKenzie, Grant; Zhang, Hongyu

Platial k-anonymity: Improving location anonymity through temporal popularity signatures Best Paper Proceedings Article

In: Proceedings of the 12th International Conference on Geographic Information Science, Schloss Dagstuhl -- Leibniz-Zentrum fur Informatik, 2023, ISSN: 1868-8969.

Abstract | Links | BibTeX

@inproceedings{McKenzie2023b,

title = {Platial k-anonymity: Improving location anonymity through temporal popularity signatures},

author = {Grant McKenzie and Hongyu Zhang },

url = {https://drops.dagstuhl.de/opus/volltexte/2023/18904/},

issn = {1868-8969},

year  = {2023},

date = {2023-08-31},

urldate = {2023-08-31},

booktitle = {Proceedings of the 12th International Conference on Geographic Information Science},

volume = {277},

publisher = {Schloss Dagstuhl -- Leibniz-Zentrum fur Informatik},

series = {Leibniz International Proceedings in Informatics (LIPIcs)},

abstract = {While it is increasingly necessary in today's digital society, sharing personal location information comes at a cost.  Sharing one's precise place of interest, e.g., Compass Coffee, enables a range of location-based services, but substantially reduces the individual's privacy.  Methods have been developed to obfuscate and anonymize location data while still maintaining a degree of utility.  One such approach, spatial k-anonymity, aims to ensure an individual's level of anonymity by reporting their location as a set of k potential locations rather than their actual location alone.  Larger values of k increase spatial anonymity while decreasing the utility of the location information.  Typical examples of spatial k-anonymized datasets present elements as simple geographic points with no attributes or contextual information.  In this work, we demonstrate that the addition of publicly available contextual data can significantly reduce the anonymity of a k-anonymized dataset.  Through the analysis of place type temporal visitation patterns, hours of operation, and popularity values, one's anonymity can decreased by more than 50 percent.  We propose a platial k-anonymity approach that leverages a combination of temporal popularity signatures and report the amount that k must increase in order to maintain a certain level of anonymity. Finally, a method for reporting platial k-anonymous regions is presented and the implications of our methods are discussed.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

Qiang, Dan; McKenzie, Grant

Mobility Vitality: Assessing Neighborhood Similarity Through Transportation Patterns In New York City Proceedings Article

In: Proceedings of the 12th International Conference on Geographic Information Science, Schloss Dagstuhl -- Leibniz-Zentrum fur Informatik, 2023.

Abstract | BibTeX

Brunila, Mikael; Verma, Priyanka; McKenzie, Grant

When Everything Is "Nearby": How Airbnb Listings in New York City Exaggerate Proximity Proceedings Article

In: Proceedings of the 12th International Conference on Geographic Information Science, Schloss Dagstuhl -- Leibniz-Zentrum fur Informatik, 2023.

Abstract | Links | BibTeX