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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/20226

Title: Helping Computers Understand Geographically-Bound Activity Restrictions
Authors: Soll, Marcus
Naumann, Philipp
Schöning, Johannes
Samsonov, Pavel
Hecht, Brent
Issue Date: 2016
Publisher: ACM
Citation: Proceedings of the International Conference on Human Factors in Computing Systems, (2016)
Abstract: The lack of certain types of geographic data prevents the development of location-aware technologies in a number of important domains. One such type of “unmapped” geographic data is space usage rules (SURs), which are defined as geographically-bound activity restrictions (e.g. “no dogs”, “no smoking”, “no fishing”, “no skateboarding”). Researchers in the area of humancomputer interaction have recently begun to develop techniques for the automated mapping of SURs with the aim of supporting activity planning systems (e.g. one-touch “Can I Smoke Here?” apps, SUR-aware vacation planning tools). In this paper, we present a novel SUR mapping technique – SPtP – that outperforms state-of-the-art approaches by 30% for one of the most important components of the SUR mapping pipeline: associating a point observation of a SUR (e.g. a ’no smoking’ sign) with the corresponding polygon in which the SUR applies (e.g. the nearby park or the entire campus on which the sign is located). This paper also contributes a series of new SUR benchmark datasets to help further research in this area.
Notes: Soll, M (reprint author), Univ Hamburg, Hamburg, Germany. 2soll@informatik.uni-hamburg.de; 2naumann@informatik.uni-hamburg.de; Johannes.Schoning@uhasselt.be; Pavel.Samsonov@uhasselt.be; bhecht@cs.umn.edu
URI: http://hdl.handle.net/1942/20226
DOI: 10.1145/2858036.2858053
ISI #: 000380532902043
ISBN: 978-1-4503- 3362-7
Category: C1
Type: Proceedings Paper
Validation: ecoom, 2017
Appears in Collections: Research publications

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