In the last two decades, the continuous increase of computational power has produced an
overwhelming flow of data which has called for a paradigm shift in the computing …

Clustering algorithms have become one of the most critical research areas in multiple
domains, especially data mining. However, with the massive growth of big data applications …

Detecting anomalies in data is a vital task, with numerous high-impact applications in areas
such as security, finance, health care, and law enforcement. While numerous techniques …

Big Data concern large-volume, complex, growing data sets with multiple, autonomous
sources. With the fast development of networking, data storage, and the data collection …

In large social networks, nodes (users, entities) are influenced by others for various reasons.
For example, the colleagues have strong influence on one's work, while the friends have …

How can web services that depend on user generated content discern fraudulent input by
spammers from legitimate input? In this paper we focus on the social network Facebook and …

In this paper, we describe PEGASUS, an open source peta graph mining library which
performs typical graph mining tasks such as computing the diameter of the graph, computing …

Many data are modeled as tensors, or multi dimensional arrays. Examples include the
predicates (subject, verb, object) in knowledge bases, hyperlinks and anchor texts in the …

As there is an increasing trend of applications being expected to deal with big data that
usually do not fit in the main memory of a single machine, analyzing big data is a …

Given a real world graph, how should we lay-out its edges? How can we compress it? These
questions are closely related, and the typical approach so far is to find clique-like …