The age of big data is now coming. But the traditional data analytics may not be able to
handle such large quantities of data. The question that arises now is, how to develop a high …

It sounds like mission impossible to connect everything on the earth together via internet, but
Internet of Things (IoT) will dramatically change our life in the foreseeable future, by making …

Clustering has become an increasingly important and highly complicated research area for
targeting useful and relevant information in modern application domains such as the World …

Clustering is one of the main methods for getting insight on the underlying nature and
structure of data. The purpose of clustering is organizing a set of data into clusters, such that …

Most clustering algorithms become ineffective when provided with unsuitable parameters or
applied to datasets which are composed of clusters with diverse shapes, sizes, and …

Abstract Information flows in a network where individuals influence each other. In this paper,
we study the influence maximization problem of finding a small subset of nodes in a social …

Determining the number of clusters, which is usually approved by domain experts or
evaluated by clustering validity indexes, is an important issue in clustering analysis. This …

Recommender systems (RS) play a crucial role in aiding decision-making by filtering
information and reducing information overload. Multiple approaches such as collaborative …

In this paper we propose a criterion to balance the processing time and the solution quality
of k-means cluster algorithms when applied to instances where the number n of objects is …

Distributed data processing platforms for cloud computing are important tools for large-scale
data analytics. Apache Hadoop MapReduce has become the de facto standard in this …