کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10344514 | 697802 | 2013 | 14 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Enabling real-time city sensing with kernel stream oracles and MapReduce
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
شبکه های کامپیوتری و ارتباطات
پیش نمایش صفحه اول مقاله
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چکیده انگلیسی
An algorithmic architecture for kernel-based modelling of data streams from city sensing infrastructures is introduced. It is both applicable for pre-installed, moving and extemporaneous sensors, including the “citizen-as-a-sensor” view on user-generated data. The approach is centred around a kernel dictionary implementing a general hypothesis space which is updated incrementally, accounting for memory and processing capacity limitations. It is general for both kernel-based classification and regression. An extension to area-to-point modelling is introduced to account for the data aggregated over a spatial region. A distributed implementation realised under the Map-Reduce framework is presented to train an ensemble of sequential kernel learners.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pervasive and Mobile Computing - Volume 9, Issue 5, October 2013, Pages 708-721
Journal: Pervasive and Mobile Computing - Volume 9, Issue 5, October 2013, Pages 708-721
نویسندگان
Christian Kaiser, Alexei Pozdnoukhov,