Fog computing is a paradigm that brings computational resources and services to the
network edge in the vicinity of user devices, lowering latency and connecting with cloud …

Nowadays, being in digital era the data generated by various applications are increasing
drastically both row-wise and column wise; this creates a bottleneck for analytics and also …

A comprehensive update of the leading algorithms text, with new material on matchings in
bipartite graphs, online algorithms, machine learning, and other topics. Some books on …

Feature selection has been the focus of interest for quite some time and much work has
been done. With the creation of huge databases and the consequent requirements for good …

THE LEGACYFirst introduced in 1995, Cryptography: Theory and Practice garnered
enormous praise and popularity, and soon became the standard textbook for cryptography …

The theory of directed graphs has developed enormously over recent decades, yet this book
(first published in 2000) remains the only book to cover more than a small fraction of the …

This paper introduces concepts and algorithms of feature selection, surveys existing feature
selection algorithms for classification and clustering, groups and compares different …

Recently, feature selection and dimensionality reduction have become fundamental tools for
many data mining tasks, especially for processing high-dimensional data such as gene …

Relevant feature identification has become an essential task to apply data mining algorithms
effectively in real-world scenarios. Therefore, many feature selection methods have been …

Feature selection is an effective technique in dealing with dimensionality reduction. For
classification, it is used to find an “optimal” subset of relevant features such that the overall …