@inproceedings{b9879a3c071d42caadde940f5733121c,
title = "Parameterized spatial query processing based on social probabilistic clustering",
abstract = "In this paper, we propose two parameterized frameworks, namely the Uniform Watchtower (UW) framework and the Hot zonebased Watchtower (HW) framework, for the evaluation of spatial queries on large road networks. The motivation of this research is twofold: (1) how to answer spatial queries efficiently on large road networks with massive POI data and (2) how to take advantage of social data in spatial query processing. In UW, the network traversal terminates once it acquires the Point of Interest (POI) distance information stored in watchtowers. In HW, by observing that users' movements often exhibit strong spatial patterns, we employ probabilistic clustering to model mobile user check-in data as a mixture of 2-dimensional Gaussian distributions to identify hot zones so that watchtowers can be deployed discriminatorily. Our analyses verify the superiority of HW over UW in terms of query response time.",
keywords = "Road networks, Spatial query",
author = "Liang Tang and Haiquan Chen and Ku, {Wei Shinn} and Sun, {Min Te}",
note = "Publisher Copyright: Copyright 2014 ACM.; 22nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2014 ; Conference date: 04-11-2014 Through 07-11-2014",
year = "2014",
month = nov,
day = "4",
doi = "10.1145/2666310.2666428",
language = "???core.languages.en_GB???",
series = "GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems",
publisher = "Association for Computing Machinery",
pages = "397--400",
editor = "Markus Schneider and Michael Gertz and Yan Huang and Jagan Sankaranarayanan and John Krumm",
booktitle = "22nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2014",
}