@techreport{TD:101693,
	att_abstract={{From economics to sports to entertainment and social media, ranking objects according to some notion of importance is a fundamental tool we humans use all the time to better understand our world. With the ever-increasing amount of user-generated content found online, “what’s trending” is now a commonplace phrase that tries to capture the zeitgeist of the world by ranking the most popular microblogging hashtags. However, before we can understand what these rankings tell us, we need to be able to more easily create and explore them, given the significant scale of today’s data. In this paper, we describe the computational challenges in building a real-time visual exploratory tool for finding top-ranked objects, build on the recent work involving in-memory and rank-aware data cubes to propse TOPKUBE, and demonstrate the usefulness of our methods using real-world, publicly available datasets.}},
	att_authors={ll447y, jk140f},
	att_categories={C_BB.1, C_IIS.7, C_IIS.1},
	att_copyright={{}},
	att_copyright_notice={{}},
	att_donotupload={},
	att_private={false},
	att_projects={IV_INFOVIS},
	att_tags={Data cube,  data structures,  interactive exploration,  ranking},
	att_techdoc={true},
	att_techdoc_key={TD:101693},
	att_url={http://web1.research.att.com:81/techdocs_downloads/TD:101693_DS1_2015-09-10T14:32:38.155Z.pdf},
	author={Lauro Lins and James Klosowski and Fabio Miranda and Claudio Silva},
	institution={{The 1st Workshop on Data Systems for Interactive Analysis}},
	month={October},
	title={{TopKube: A Rank-Aware Data Cube for Real-Time Exploration of Spatiotemporal Datasets}},
	year=2015,
}