@inproceedings{0dca3e4f43744ada8f5171c0b7e74c0e,
title = "ADCN: An anisotropic density-based clustering algorithm",
abstract = "In this work we introduce an anisotropic density-based clustering algorithm. It outperforms DBSCAN and OPTICS for the detection of anisotropic spatial point patterns and performs equally well in cases that do not explicitly benefit from an anisotropic perspective. ADCN has the same time complexity as DBSCAN and OPTICS, namely O(n log n) when using a spatial index, O(n2) otherwise.",
author = "Gengchen Mai and Krzysztof Janowicz and Yingjie Hu and Song Gao",
note = "Publisher Copyright: {\textcopyright} 2016 ACM.; 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2016 ; Conference date: 31-10-2016 Through 03-11-2016",
year = "2016",
month = oct,
day = "31",
doi = "10.1145/2996913.2996940",
language = "English",
series = "GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems",
publisher = "Association for Computing Machinery ",
editor = "Matthias Renz and Mohamed Ali and Shawn Newsam and Matthias Renz and Siva Ravada and Goce Trajcevski",
booktitle = "24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2016",
address = "United States",
}