کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
465588 | 697638 | 2015 | 22 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Automatically recognizing places of interest from unreliable GPS data using spatio-temporal density estimation and line intersections
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
شبکه های کامپیوتری و ارتباطات
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چکیده انگلیسی
Stay points are important for recognizing significant places from a mobile user’s GPS trajectory. Such places are often located indoors and in urban canyons, where GPS is unreliable. Consequently, mapping a user’s stay point to a Place of Interest (POI) using only GPS data is particularly challenging. Our novel algorithm employs both spatio-temporal density estimation and line count inference to predict and rank a user’s POI(s) at building level accuracy from noisy time-annotated GPS data points. An experimental study demonstrates the superiority of our algorithm against several baseline approaches with a recall of 96.5% for the top 5 retrieved locations.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pervasive and Mobile Computing - Volume 19, May 2015, Pages 86–107
Journal: Pervasive and Mobile Computing - Volume 19, May 2015, Pages 86–107
نویسندگان
Tanusri Bhattacharya, Lars Kulik, James Bailey,