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Artificial intelligence applications in information and communication technologies
Laalaoui Y., Bouguila N., Springer International Publishing, New York, NY, 2015. 213 pp. Type: Book (978-3-319198-32-3)
Date Reviewed: Jul 8 2016

According to analysts, data volumes are expected to grow 44 fold in a decade (2011-2020). The variety of the data, along with the speed with which it is generated in an increasingly connected world, makes artificial intelligence (AI)-driven solutions crucial to the development of state-of-the-art systems.

Hence, a book on AI applications in information and communication technologies (ICT) is highly timely and relevant. Although the ICT term is rather generic, the book has in fact an orientation toward computer network applications. The book is a collection of nine papers, each written by a different set of authors, and sectioned into three parts, each one presenting different applications in three areas of AI: “Search and Optimization,” “Machine Learning,” and “Ontologies and Multi-Agents.”

In Part 1, “Search and Optimization,” three different applications of these techniques are presented in the broader area of computer systems: the use of meta-heuristics for resource management and job scheduling in high-performance computing clusters and grids; the use of ant colony optimization (ACO) approaches to information retrieval; and the use of a combinatorial optimization approach to optimize resource allocation in application service provider data centers. Overall, this part is well written, with clear algorithms and experimental results on real data.

Part 2, “Machine Learning,” starts with a paper that is highly relevant to the aim of the book, which presents the applications of AI in diverse domains such as telecommunications, virus epidemic prediction, smart building energy management, cloud robotics, client profiling, and alarm prediction in telecommunication networks. The two problem areas covered by these applications--the Internet of Things (IoT) and telecommunication networks--are areas of strong research and industrial interest.

The rest of Part 2--that is, the remaining three papers--pertain to the area of computer vision. More specifically, they propose data models based on the generalized inverted Dirichlet mixture and apply them to different problems within the area of computer vision. As such, this part of the book is rather focused on a specific methodology (Dirichlet mixture models) applied to a specific area. All three papers are not for a general ICT audience as they are heavy in mathematics. However, having said that, the problems they are solving are important, challenging, and interesting in their own right, for example, building an interactive system to search for the mental image target of the user, or the classification of human activity.

The last part of the book, “Ontologies and Multi-Agents,” consists of only two papers. The first paper is on the configuration of network devices using an ontology-based information extraction system that utilizes natural language processing (NLP) techniques to extract relevant information and build semantics from the command-line interface (CLI). The second paper is on industrial sustainability, where the authors propose a system that will assist managers in making the best decisions in the different stages of the product life cycle, incorporating expert systems to manage the knowledge related to environmental regulations.

Overall, the majority of the book reads well. It will be of most interest to researchers in computer networks, with the exception of Part 2, which as I mentioned is on a different field and for a more specific audience.

Reviewer:  Athena Stassopoulou Review #: CR144560 (1609-0646)
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Multiagent Systems (I.2.11 ... )
 
 
Computer Vision (I.5.4 ... )
 
 
Data Communications (C.2.0 ... )
 
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