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» Data streams: algorithms and applications
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186
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SIGMOD
2006
ACM
110views Database» more  SIGMOD 2006»
16 years 28 days ago
Finding k-dominant skylines in high dimensional space
Given a d-dimensional data set, a point p dominates another point q if it is better than or equal to q in all dimensions and better than q in at least one dimension. A point is a ...
Chee Yong Chan, H. V. Jagadish, Kian-Lee Tan, Anth...
PODS
2002
ACM
167views Database» more  PODS 2002»
16 years 28 days ago
OLAP Dimension Constraints
In multidimensional data models intended for online analytic processing (OLAP), data are viewed as points in a multidimensional space. Each dimension has structure, described by a...
Carlos A. Hurtado, Alberto O. Mendelzon
ALT
2009
Springer
15 years 9 months ago
Average-Case Active Learning with Costs
Abstract. We analyze the expected cost of a greedy active learning algorithm. Our analysis extends previous work to a more general setting in which different queries have differe...
Andrew Guillory, Jeff A. Bilmes
108
Voted
ICDE
2010
IEEE
177views Database» more  ICDE 2010»
15 years 7 months ago
Optimal load shedding with aggregates and mining queries
— To cope with bursty arrivals of high-volume data, a DSMS has to shed load while minimizing the degradation of Quality of Service (QoS). In this paper, we show that this problem...
Barzan Mozafari, Carlo Zaniolo
101
Voted
IUI
2009
ACM
15 years 7 months ago
Discovering frequent work procedures from resource connections
Intelligent desktop assistants could provide more help for users if they could learn models of the users’ workflows. However, discovering desktop workflows is difficult becau...
Jianqiang Shen, Erin Fitzhenry, Thomas G. Dietteri...
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