Community detection is a fundamental problem in social network analysis consisting,
roughly speaking, in unsupervised dividing social actors (modeled as nodes in a social …

Distributed data aggregation is an important task, allowing the decentralized determination
of meaningful global properties, which can then be used to direct the execution of other …

Abstract Methods for Approximate Query Processing (AQP) are essential for dealing with
massive data. They are often the only means of providing interactive response times when …

Propagation of contagion through networks is a fundamental process. It is used to model the
spread of information, influence, or a viral infection. Diffusion patterns can be specified by a …

We study the problem of domain search where a domain is a set of distinct values from an
unspecified universe. We use Jaccard set containment, defined as $| Q\cap X|/| Q| $, as the …

Sketch techniques have undergone extensive development within the past few years. They
are especially appropriate for the data streaming scenario, in which large quantities of data …

As a key problem in viral marketing, influence maximization has been extensively studied in
the literature. Given a positive integer, a social network and a certain propagation model, it …

We introduce and study a new data sketch for processing massive datasets. It addresses two
common problems: 1) computing a sum given arbitrary filter conditions and 2) identifying the …

Closeness centrality, first considered by Bavelas (1948), is an importance measure of a
node in a network which is based on the distances from the node to all other nodes. The …

A sliding windows model is an important case of the streaming model, where only the most"
recent" elements remain active and the rest are discarded in a stream. The sliding windows …