Finding frequent items in probabilistic data

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Finding frequent items in probabilistic data
Computing statistical information on probabilistic data has attracted a lot of attention recently, as the data generated from a wide range of data sources are inherently fuzzy or uncertain. In this paper, we study an important statistical query on probabilistic data: finding the frequent items. One straightforward approach to identify the frequent items in a probabilistic data set is to simply compute the expected frequency of an item and decide if it exceeds a certain fraction of the expected size of the whole data set. However, this simple definition misses important information about the internal structure of the probabilistic data and the interplay among all the uncertain entities. Thus, we propose a new definition based on the possible world semantics that has been widely adopted for many query types in uncertain data management, trying to find all the items that are likely to be frequent in a randomly generated possible world. Our approach naturally leads to the study of ranking...
Qin Zhang, Feifei Li, Ke Yi
Added 08 Dec 2009
Updated 08 Dec 2009
Type Conference
Year 2008
Authors Qin Zhang, Feifei Li, Ke Yi
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