This is a tremendously important paper for insight into how computer
scientists are trying to model and sense human concepts of place... In some
ways, its a computerization of Kevin Lynch's mental mapping methods from the
50s and 60s (e.g. "Good City Form")


http://www.placelab.org/publications/pubs/beaconprint2005-placelab.pdf

Learning and Recognizing the Places We Go
Jeffrey Hightower, Sunny Consolvo, Anthony LaMarca, Ian Smith, and
Jeff Hughes 

Intel Research Seattle
University of Washington
Seattle, WA, USA Computer Science & Engineering
Seattle, WA, USA 

Abstract. 

Location-enhanced mobile devices are becoming common,
but applications built for these devices find themselves suffering a mis-
match between the latitude and longitude that location sensors provide
and the colloquial place label that applications need. Conveying my loca-
tion to my spouse, for example as (48.13641N, 11.57471E), is less infor-
mative than saying ³at home.² We introduce an algorithm called Beacon-
Print that uses WiFi and GSM radio fingerprints collected by someone¹s
personal mobile device to automatically learn the places they go and
then detect when they return to those places. BeaconPrint does not au-
tomatically assign names or semantics to places. Rather, it provides the
technological foundation to support this task. We compare BeaconPrint
to three existing algorithms using month-long trace logs from each of
three people. Algorithmic results are supplemented with a survey study
about the places people go. BeaconPrint is over 90% accurate in learning
and recognizing places. Additionally, it improves accuracy in recogniz-
ing places visited infrequently or for short durations‹a category where
previous approaches have fared poorly. BeaconPrint demonstrates 63%
accuracy for places someone returns to only once or visits for less than
10 minutes, increasing to 80% accuracy for places visited twice. 



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