While advances in computing resources have made processing enormous amounts of data
possible, human ability to identify patterns in such data has not scaled accordingly. Efficient …

Evolutionary network analysis has found an increasing interest in the literature because of
the importance of different kinds of dynamic social networks, email networks, biological …

In massive and rapid graph streams, a useful and important task is to summarize the
structure of graph streams in order to enable efficient and effective graph query processing …

Approximated algorithms are often used to estimate the frequency of items on high volume,
fast data streams. The most common ones are variations of Count-Min sketch, which use sub …

Recording the frequency of items in highly skewed data streams is a fundamental and hot
problem in recent years. The literature demonstrates that sketch is the most promising …

Sampling is a standard approach in big-graph analytics; the goal is to efficiently estimate the
graph properties by consulting a sample of the whole population. A perfect sample is …

A graph stream, which refers to the graph with edges being updated sequentially in a form of
a stream, has important applications in cyber security and social networks. Due to the sheer …

This paper studies I/O-efficient algorithms for settling the classic triangle listing problem,
whose solution is a basic operator in dealing with many other graph problems. Specifically …

Due to the growing need to process large graph and network datasets created by modern
applications, recent years have witnessed a surging interest in developing big graph …

Given a fully dynamic graph, represented as a stream of edge insertions and deletions, how
can we obtain and incrementally update a lossless summary of its current snapshot? As …