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

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 …

Uncertain data is inherent in a few important applications such as environmental
surveillance and mobile object tracking. Top-k queries (also known as ranking queries) are …

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 …

When dealing with massive quantities of data, top-k queries are a powerful technique for
returning only the k most relevant tuples for inspection, based on a scoring function. The …

Preferences have been traditionally studied in philosophy, psychology, and economics and
applied to decision making problems. Recently, they have attracted the attention of …

Uncertain data are inherent in some important applications, such as environmental
surveillance, market analysis, and quantitative economics research. Due to the importance …

The dramatic growth in the number of application domains that naturally generate
probabilistic, uncertain data has resulted in a need for efficiently supporting complex …

Skyline queries are a popular way to obtain preferred answers from the database by
providing only the orderings of attribute values. The result of a skyline query consists of …

Probabilistic data is motivated by the need to model uncertainty in large databases. Over the
last twenty years or so, both the Database community and the AI community have studied …