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Title: | Helping Computers Understand Geographically-Bound Activity Restrictions | Authors: | Soll, Marcus Naumann, Philipp SCHOENING, Johannes SAMSONOV, Pavel Hecht, Brent |
Issue Date: | 2016 | Publisher: | ACM | Source: | 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 | Keywords: | Space Usage Rules (SUR); location-aware technologies | Document URI: | http://hdl.handle.net/1942/20226 | ISBN: | 978-1-4503- 3362-7 | DOI: | 10.1145/2858036.2858053 | ISI #: | 000380532902043 | Rights: | Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from Permissions@acm.org. CHI'16, May 07 - 12, 2016, San Jose, CA, USA Copyright is held by the owner/author(s). Publication rights licensed to ACM. | Category: | C1 | Type: | Proceedings Paper | Validations: | ecoom 2017 |
Appears in Collections: | Research publications |
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File | Description | Size | Format | |
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paper207.pdf | Peer-reviewed author version | 385.37 kB | Adobe PDF | View/Open |
2858036.2858053.pdf Restricted Access | Published version | 774.3 kB | Adobe PDF | View/Open Request a copy |
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