Uncertainty accompanies our life processes and covers almost all fields of scientific studies.
Two general categories of uncertainty, namely, aleatory uncertainty and epistemic …

Probabilistic databases are databases where the value of some attributes or the presence of
some records are uncertain and known only with some probability. Applications in many …

Complex networks, such as biological, social, and communication networks, often entail
uncertainty, and thus, can be modeled as probabilistic graphs. Similar to the problem of …

We study in this paper provenance information for queries with aggregation. Provenance
information was studied in the context of various query languages that do not allow for …

In many real applications, graph data is subject to uncertainties due to incompleteness and
imprecision of data. Mining such uncertain graph data is semantically different from and …

Uncertain data are data with uncertainty information, which exist widely in database
applications. In recent years, uncertainty in data has brought challenges in almost all …

We study the problem of clustering probabilistic graphs. Similar to the problem of clustering
standard graphs, probabilistic graph clustering has numerous applications, such as finding …

Traditional rank-aware processing assumes a dataset that contains available options to
cover a specific need (eg, restaurants, hotels, etc) and users who browse that dataset via top …

Reverse top-k queries are proposed from the perspective of a product manufacturer, which
are essential for manufacturers to assess the potential market. However, the existing …

There has been an increasing growth in numerous applications that naturally generate large
volumes of uncertain data. By the advent of such applications, the support of advanced …