@techreport{TD:100397,
	att_abstract={{Understanding the mix of different types of people in a city is an important input into urban planning.  In this paper we identify distinct sectors of a population by their cellular phone usage.  In a study of a small suburban city in New Jersey, we use unsupervised clustering to identify the usage patterns of heavy users .  We uncover 7 unique usage patterns.  We  interpret two of the patterns as belonging to commuters and students, and verify these interpretations with deeper analysis of temporal and spatial patterns.  }},
	att_authors={cv2452, rb2812, rc177e, kh1285, jl213k, su2464, av8693},
	att_categories={},
	att_copyright={{Springer}},
	att_copyright_notice={{The definitive version was published in  PURBA-2011. {{, 2011-06-12}}
}},
	att_donotupload={},
	att_private={false},
	att_projects={ SagaCITY, A_Tale_of_One_City},
	att_tags={},
	att_techdoc={true},
	att_techdoc_key={TD:100397},
	att_url={http://web1.research.att.com:81/techdocs_downloads/TD:100397_DS1_2011-02-16T22:13:21.594Z.pdf},
	author={Christopher Volinsky and Richard Becker and Ramon Caceres and Karrie Hanson and Ji Loh and Simon Urbanek and Alexander Varshavsky},
	institution={{1st Workshop on Pervasive Urban Applications (PURBA)}},
	month={June},
	title={{Clustering Anonymized Mobile Call Detail Records to Find Usage Groups}},
	year=2011,
}