This chapter reviews applications of Memetic Algorithms in the areas of business analytics
and data science. This approach originates from the need to address optimization problems …

Community detection is an exciting field of research which has attracted the interest of many
researchers during the last decade. While many algorithms and heuristics have been …

In this study we propose a novel, unsupervised clustering methodology for analyzing large
datasets. This new, efficient methodology converts the general clustering problem into the …

In this paper, we present a new Memetic Algorithm for overlapping community detection. We
use a link-based clustering approach to detect the communities of edges in complex …

In this paper, we examine if the Relative Neighborhood Graph (RNG) can reveal related
dynamics of page-level social media metrics. A statistical analysis is also provided to …

Motivated by the celebrated paper of Hooker (J Heuristics 1 (1): 33–42, 1995) published in
the first issue of this journal, and by the relative lack of progress of both approximation …

A large number of problems in business and consumer analytics have input graphs or
networks. These mathematical entities have a long standing tradition in discrete applied …

In recent years, the use of data analytics is widely documented for its use in for-profit
businesses. So too have risen open data initiatives, calls for the ethical use of data, and its …

Social media has almost become ubiquitous in everyday communications and interactions
between customers and brands. A novel clustering algorithm, that has shown high scalability …

This extended appendix provides information, summaries and methodological details for
publicly available datasets and, in particular, those used by various authors throughout this …