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An experiment in discovering personally meaningful places from location data

Published: 02 April 2005 Publication History

Abstract

As mobile devices become location-aware, they offer the promise of powerful new applications. While computers work with physical locations like latitude and longitude, people think and speak in terms of places, like "my office" or ``Sue's house''. Therefore, location-aware applications must incorporate the notion of places to achieve their full potential. This requires systems to acquire the places that are meaningful for each user. Previous work has explored algorithms to discover personal places from location data. However, we know of no empirical, quantitative evaluations of these algorithms, so the question of how well they work currently is unanswered. We report here on an experiment that begins to provide an answer; we show that a place discovery algorithm can do a good job of discovering places that are meaningful to users. The results have important implications for system design and open up interesting avenues for future research.

References

[1]
D. Ashbrook and T. Starner. Learning significant locations and predicting user movement with GPS. In Proc. IEEE Sixth International Symposium on Wearable Computing, 2002.]]
[2]
K. A. Franck and L. H. Schneekloth, editors. Ordering space: types in architecture and design. Van Nostrand Reinhold, 1994.]]
[3]
R. Genereux, L. Ward, and J. Russell. The behavioral component in the meaning of places. Journal of Environmental Psychology, 3:43--55, 1983.]]
[4]
J. Hightower. From position to place. In Proc. Workshop on Location-Aware Computing, 2003.]]
[5]
B. Kramer. Classification of generic places: Explorations with implications for evaluation. Journal of Environmental Psychology, 15:3--22, 1995.]]
[6]
L. Liao, D. Fox, and H. Kautz. Learning and inferring transportation routines. In Proc. AAAI, 2004.]]
[7]
S. Long, R. Kooper, G. D. Abowd, and C. G. Atkeson. Rapid prototyping of mobile context-aware applications: The cyberguide case study. In Proc. MobiCom, pages 97--107, 1996.]]
[8]
N. Marmasse and C. Schmandt. Location-aware information delivery with commotion. In Proc. HUC, pages 157--171, 2000.]]
[9]
M. Naaman, Y. J. Song, A. Paepcke, and H. Garcia-Molina. Automatic organization for digital photographs with geographic coordinates. In Proc. JCDL, 2004.]]
[10]
D. Patterson, L. Liao, D. Fox, and H. Kautz. Inferring high-level behavior from low-level sensors. In Proc. UbiComp, 2003.]]
[11]
J. Rieman. The diary study: a workplace-oriented research tool to guide laboratory efforts. In Proc. CHI, 1993.]]
[12]
A. H. Weilenmann and P. Leuchovius. I'm waiting where we met last time: exploring everyday positioning practices to inform design. In Proc. NordiCHI, 2004.]]
[13]
C. Zhou, D. Frankowski, P. Ludford, S. Shekhar, and L. Terveen. Discovering personal gazetteers: An interactive clustering approach. In Proc. ACMGIS, 2004.]]

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    cover image ACM Conferences
    CHI EA '05: CHI '05 Extended Abstracts on Human Factors in Computing Systems
    April 2005
    1358 pages
    ISBN:1595930027
    DOI:10.1145/1056808
    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 ACM 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 [email protected]

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    Published: 02 April 2005

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    Author Tags

    1. clustering algorithms
    2. field studies
    3. location-aware applications
    4. place discovery
    5. ubiquitous computing

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    Cited By

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    • (2022)A Novel Method for Groups Identification Based on Spatio-Temporal TrajectoriesSpatial Data and Intelligence10.1007/978-3-031-24521-3_19(264-280)Online publication date: 5-Aug-2022
    • (2020)Understanding Citywide Resident Mobility Using Big Data of Electronic Registration Identification of VehiclesIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2019.294072421:10(4363-4377)Online publication date: Oct-2020
    • (2020)A Framework of Input Devices to Support Designing Composite Wearable ComputersHuman-Computer Interaction. Multimodal and Natural Interaction10.1007/978-3-030-49062-1_28(401-427)Online publication date: 10-Jul-2020
    • (2017)A Framework Supporting Selecting Space to Make Place in Spatial Mixed Reality PlayProceedings of the Annual Symposium on Computer-Human Interaction in Play10.1145/3116595.3116612(83-100)Online publication date: 15-Oct-2017
    • (2017)Wi-Vision: An Accurate and Robust LOS/NLOS Identification System Using Hopkins StatisticGLOBECOM 2017 - 2017 IEEE Global Communications Conference10.1109/GLOCOM.2017.8254601(1-6)Online publication date: Dec-2017
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    • (2013)Automated urban location annotation on mobile records2013 10th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)10.1109/FSKD.2013.6816332(951-956)Online publication date: Jul-2013
    • (2013)iReminder: An Intuitive Location-Based Reminder That Knows Where You Are GoingInternational Journal of Human-Computer Interaction10.1080/10447318.2013.79644029:12(838-850)Online publication date: 2-Dec-2013
    • (2013)“Place” and “Non-Place”: A Model for the Strategic Design of Place-Centered ServicesBell Labs Technical Journal10.1002/bltj.2157217:4(21-36)Online publication date: 27-Feb-2013
    • (2010)Modeling people's place naming preferences in location sharingProceedings of the 12th ACM international conference on Ubiquitous computing10.1145/1864349.1864362(75-84)Online publication date: 26-Sep-2010
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