@inproceedings{a-noise-map-of-new-york-city,
author = {Wang, Yilun and Zheng, Yu and Liu, Tong},
title = {A Noise Map of New York City},
booktitle = {UbiComp 2014},
year = {2014},
month = {August},
abstract = {

This demonstration presents a noise map of New York City, based on four ubiquitous data sources: 311 complaint data, social media, road networks, and Point of Interests (POIs). The noise situation of any location in the city, consisting of a noise pollution indicator and a noise composition, is derived through a context-aware tensor decomposition approach we proposed in [5]. Moreover, our demo highlights two components: a) ranking locations based on inferred noise indicators in various settings, e.g., on the weekdays (or weekends), in a time slot (or overall time), and in a noise category (or all categories); b) revealing the distribution of noises over different noise categories in a location.

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[video width="854" height="480" mp4="https://www.microsoft.com/en-us/research/wp-content/uploads/2014/09/urban_noise_ubicomp2011_yuzheng.mp4"][/video]


},
publisher = {Demo Paper at UbiComp 2014},
url = {https://www.microsoft.com/en-us/research/publication/a-noise-map-of-new-york-city/},
address = {},
pages = {},
journal = {},
volume = {},
chapter = {},
isbn = {},
}