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» OLAP Over Uncertain and Imprecise Data
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SSD
2007
Springer
132views Database» more  SSD 2007»
13 years 11 months ago
Computing a k -Route over Uncertain Geographical Data
An uncertain geo-spatial dataset is a collection of geo-spatial objects that do not represent accurately real-world entities. Each object has a confidence value indicating how lik...
Eliyahu Safra, Yaron Kanza, Nir Dolev, Yehoshua Sa...
SIGMOD
2008
ACM
158views Database» more  SIGMOD 2008»
14 years 5 months ago
Sampling cube: a framework for statistical olap over sampling data
Sampling is a popular method of data collection when it is impossible or too costly to reach the entire population. For example, television show ratings in the United States are g...
Xiaolei Li, Jiawei Han, Zhijun Yin, Jae-Gil Lee, Y...
SIGMOD
2003
ACM
145views Database» more  SIGMOD 2003»
14 years 5 months ago
Evaluating Probabilistic Queries over Imprecise Data
Many applications employ sensors for monitoring entities such as temperature and wind speed. A centralized database tracks these entities to enable query processing. Due to contin...
Reynold Cheng, Dmitri V. Kalashnikov, Sunil Prabha...
EDBT
2009
ACM
207views Database» more  EDBT 2009»
13 years 8 months ago
Evaluating probability threshold k-nearest-neighbor queries over uncertain data
In emerging applications such as location-based services, sensor monitoring and biological management systems, the values of the database items are naturally imprecise. For these ...
Reynold Cheng, Lei Chen 0002, Jinchuan Chen, Xike ...
EUSFLAT
2007
117views Fuzzy Logic» more  EUSFLAT 2007»
13 years 6 months ago
Transforming Probability Intervals into Other Uncertainty Models
Probability intervals are imprecise probability assignments over elementary events. They constitute a very convenient tool to model uncertain information : two common cases are co...
Sébastien Destercke, Didier Dubois, Eric Ch...