Significant research efforts have recently been dedicated to modeling and querying uncertain data. In this paper, we focus on skyline analysis of uncertain data, modeled as uncert...
There is a large amount of data that is published on the Web and several techniques have been developed to extract and integrate data from Web sources. However, Web data are inhere...
Lorenzo Blanco, Valter Crescenzi, Paolo Merialdo, ...
Mining frequent itemsets from transactional datasets is a well known problem with good algorithmic solutions. In the case of uncertain data, however, several new techniques have be...
In an uncertain database, each data item is modeled as a range associated with a probability density function. Previous works for this kind of data have focussed on simple queries...
Classification is one of the most essential tasks in data mining. Unlike other methods, associative classification tries to find all the frequent patterns existing in the input...
Recently the academic communities have paid more attention to the queries and mining on uncertain data. In the tasks such as clustering or nearest-neighbor queries, expected distan...
We present PROUD - A PRObabilistic approach to processing similarity queries over Uncertain Data streams, where the data streams here are mainly time series streams. In contrast t...
Mi-Yen Yeh, Kun-Lung Wu, Philip S. Yu, Ming-Syan C...
Uncertain data streams, where data is incomplete, imprecise, and even misleading, have been observed in many environments. Feeding such data streams to existing stream systems pro...
Thanh T. L. Tran, Liping Peng, Boduo Li, Yanlei Di...
Uncertain data are inherent in some important applications. Although a considerable amount of research has been dedicated to modeling uncertain data and answering some types of qu...
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...