期刊
PROCEEDINGS OF THE VLDB ENDOWMENT
卷 4, 期 1, 页码 12-21出版社
ASSOC COMPUTING MACHINERY
DOI: 10.14778/1880172.1880174
关键词
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资金
- Hong Kong RGC GRF [611608]
- NSFC [60933011, 60933012]
Data uncertainty is ubiquitous in many real-world applications such as sensor/RFID data analysis. In this paper, we investigate uncertain data that exhibit local correlations, that is, each uncertain object is only locally correlated with a small subset of data, while being independent of others. We propose a generic framework for dealing with this kind of uncertain and locally correlated data, in which we investigate a classical spatial query, nearest neighbor query, on uncertain data with local correlations (namely LC-PNN). Most importantly, to enable fast LC-PNN query processing, we propose a novel filtering technique via offline pre-computations to reduce the query search space. We demonstrate through extensive experiments the efficiency and effectiveness of our approaches.
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