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

Uncertain data have already widely existed in many practical applications recently, such as
sensor networks, RFID networks, location-based services, and mobile object management …

Differential privacy (DP) is a widely accepted mathematical framework for protecting data
privacy. Simply stated, it guarantees that the distribution of query results changes only …

In recent years, a number of indirect data collection methodologies have lead to the
proliferation of uncertain data. Such data points are often represented in the form of a …

Markov Logic Networks (MLNs) have emerged as a powerful framework that combines
statistical and logical reasoning; they have been applied to many data intensive problems …

Probabilistic frequent itemset mining in uncertain transaction databases semantically and
computationally differs from traditional techniques applied to standard" certain" transaction …

To deal with data uncertainty, existing probabilistic database systems augment tuples with
attribute-level or tuple-level probability values, which are loaded into the database along …

Many applications today need to manage large data sets with uncertainties. In this paper we
describe the foundations of managing data where the uncertainties are quantified as …

This paper introduces U-relations, a succinct and purely relational representation system for
uncertain databases. U-relations support attribute-level uncertainty using vertical …

Probabilistic databases Page 1 86 communications of the acm | july 2009 | vol. 52 | no. 7
review articles they query, search, and aggregate large volumes of imprecise data to find the …