In many modern applications, there are no exact values available to describe the data objects. Instead, the feature values are considered to be uncertain.

In many modern applications, there are no exact values available to describe the data objects. Instead, the feature values are considered to be uncertain.

This paper examines a new type of queries on uncertain data objects, called probability ranking queries (PRQ), and introduces a novel index structure called ...

Jul 3, 2006 · In this paper, we examine a new type of queries on uncertain data objects, called probability ranking queries (PRQ). A PRQ retrieves those k ...

Bibliographic details on Probabilistic Ranking Queries on Gaussians.

Abstract— When dealing with massive quantities of data, top- k queries are a powerful technique for returning only the k most relevant tuples for inspection ...

We propose several filtering techniques and an R-tree-based index to efficiently support probabilistic range queries over Gaussian objects. Extensive ...

Probabilistic Range Queries (PRQ) retrieve objects which, according to imprecise object properties, are (with a given probability) inside a precise range.

Abstract—This paper introduces a scalable approach for probabilistic top-k similarity ranking on uncertain vector data. Each uncertain.

Modern enterprise applications are forced to deal with unreliable, inconsistent and imprecise information. Prob- abilistic databases can model such data ...