This book gathers extended versions of the best papers presented at the Global Joint Conference on Industrial Engineering and Its Application Areas (GJCIE), held in Nevsehir, Turkey, on June 21-22, 2018. They reports on industrial engineering methods and applications, with a special focus on the advantages and challenges posed by Big data in this field. The book covers a wide range of topics, including decision making, optimization, supply chain management and quality control.

This book constitutes the refereed proceedings of the 15th International Conference on Web Engineering, ICWE 2015, held in Rotterdam, The Netherlands, in June 2015. The 26 full research papers, 11 short papers, 7 industry papers, 11 demonstrations, 6 posters and 4 contributions to the PhD symposium presented were carefully reviewed and selected from 100 submissions. Moreover 2 tutorials are presented. The papers focus on eight tracks, namely Web application modeling and engineering; mobile Web applications; social Web applications; semantic Web applications; quality and accessibility aspects of Web applications; Web applications composition and mashups; Web user interfaces; security and privacy in Web applications.

This book constitutes the refereed proceedings of the 15th International Conference on Web Engineering, ICWE 2015, held in Rotterdam, The Netherlands, in June 2015. The 26 full research papers, 11 short papers, 7 industry papers, 11 demonstrations, 6 posters and 4 contributions to the PhD symposium presented were carefully reviewed and selected from 100 submissions. Moreover 2 tutorials are presented. The papers focus on eight tracks, namely Web application modeling and engineering; mobile Web applications; social Web applications; semantic Web applications; quality and accessibility aspects of Web applications; Web applications composition and mashups; Web user interfaces; security and privacy in Web applications.

There currently is no in-depth book dedicated to the challenge of the Internet of Everything and Big Data technologies in smart cities. Humankind today is confronting a critical worldwide portability challenge and the framework that moves cities must keep pace with the innovation. Internet of Everything and Big Data: Major Challenges in Smart Cities reviews the applications, technologies, standards, and other issues related to smart cities. This book is dedicated to addressing the major challenges in realizing smart cities and sensing platforms in the era of Big Data cities and Internet of Everything. Challenges vary from cost and energy efficiency to availability and service quality. This book examines security issues and challenges, addresses the total information science challenges, covers exploring and creating IoT environment-related sales adaptive systems, and investigates basic and high-level concepts using the latest techniques implemented by researchers and businesses. The book is written for analysts, researchers, and specialists who are working on the future generation of the technologies. It will serve as a valuable guide for those in the industry, and students as well.

Big data is marked by staggering growth in the collection and analysis of digital trace information regarding human and natural activity, bound up in and enabled by the rise of persistent connectivity, networked communication, smart machines, and the internet of things. In addition to their impact on technology and society, these developments have particular significance for the media industry and for journalism as a practice and a profession. These data-centric phenomena are, by some accounts, poised to greatly influence, if not transform, some of the most fundamental aspects of news and its production and distribution by humans and machines. What such changes actually mean for news, democracy, and public life, however, is far from certain. As such, there is a need for scholarly scrutiny and critique of this trend, and this volume thus explores a range of phenomena—from the use of algorithms in the newsroom, to the emergence of automated news stories—at the intersection between journalism and the social, computer, and information sciences. What are the implications of such developments for journalism’s professional norms, routines, and ethics? For its organizations, institutions, and economics? For its authority and expertise? And for the epistemology that underwrites journalism’s role as knowledge-producer and sense-maker in society? Altogether, this book offers a first step in understanding what big data means for journalism. This book was originally published as a special issue of Digital Journalism.

This book is one-stop shop which offers essential information one must know and can implement in real-time business expansions to solve engineering problems in various disciplines. It will also help us to make future predictions and decisions using AI algorithms for engineering problems. Machine learning and optimizing techniques provide strong insights into novice users. In the era of big data, there is a need to deal with data science problems in multidisciplinary perspective. In the real world, data comes from various use cases, and there is a need of source specific data science models. Information is drawn from various platforms, channels, and sectors including web-based media, online business locales, medical services studies, and Internet. To understand the trends in the market, data science can take us through various scenarios. It takes help of artificial intelligence and machine learning techniques to design and optimize the algorithms. Big data modelling and visualization techniques of collected data play a vital role in the field of data science. This book targets the researchers from areas of artificial intelligence, machine learning, data science and big data analytics to look for new techniques in business analytics and applications of artificial intelligence in recent businesses.