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 pro...
We apply a well-known Bayesian probabilistic model to textual information retrieval: the classification of documents based on their relevance to a query. This model was previously...
Most known constructions of probabilistically checkable proofs (PCPs) either blow up the proof size by a large polynomial, or have a high (though constant) query complexity. In thi...
Data exchange between embedded systems and other small or large computing devices increases. Since data in different data sources may refer to the same real world objects, data ca...
In this paper we present an improved version of the Probabilistic Ant based Clustering Algorithm for Distributed Databases (PACE). The most important feature of this algorithm is ...