Giner Alor-Hernandez – författare

This book presents innovative and high-quality research regarding the implementation of Semantic Web technologies for knowledge representation and developing intelligent applications in various domains. Semantic Web technologies have inspired many people to create innovative technologies and applications for knowledge representation, Semantic Searches, NLP and Social Networks. The goal of this book is to collect and consolidate novel and high-quality research contributions on Semantic Web technologies and their theoretical and practical application to a range of different domains. In addition to researchers, the book offers a valuable resource for PhD students, master and undergraduate students in IT-related fields such as Computer Science and Information Systems. 

This book presents the latest developments concerning techniques, tools, and methodologies in supply chain ecosystems. It gathers contributions from a variety of experts, who analyze a range of case studies and industrial sectors such as manufacturing, energy, agricultural, healthcare, humanitarian logistics, and urban goods distribution, to name but a few.

The book is chiefly intended to meet the needs of two sectors: firstly, the academic sector, so as to familiarize students, professors, and researchers with the tools that are now being used to optimize supply chains; and secondly, the industrial and managerial sector, so that supply chain management practitioners can benefit from methods and tools that are yielding valuable results in other contexts.

This book presents different techniques and methodologies that used to help improve the decision-making process and increase the likelihood of success in sector as follows: agriculture, financial services, logistics, energy services, health and others. 

This book presents different techniques and methodologies used to improve the intelligent decision-making process and increase the likelihood of success in companies of different sectors such as Financial Services, Education, Supply Chain, Energy Systems, Health Services, and others.

The book contains and consolidates innovative and high-quality research contributions regarding the implementation of techniques and methodologies applied in different sectors. The scope is to disseminate current trends knowledge in the implementation of artificial intelligence techniques and methodologies in different fields such as: Logistics, Software Development, Big Data, Internet of Things, Simulation, among others. The book contents are useful for Ph.D. researchers, Ph.D. students, master and undergraduate students of different areas such as Industrial Engineering, Computer Science, Information Systems, Data Analytics, and others.

This book presents innovative and high-quality research on the implementation of conceptual frameworks, strategies, techniques, methodologies, informatics platforms and models for developing advanced knowledge-based systems and their application in different fields, including Agriculture, Education, Automotive, Electrical Industry, Business Services, Food Manufacturing, Energy Services, Medicine and others.

Knowledge-based technologies employ artificial intelligence methods to heuristically address problems that cannot be solved by means of formal techniques. These technologies draw on standard and novel approaches from various disciplines within Computer Science, including Knowledge Engineering, Natural Language Processing, Decision Support Systems, Artificial Intelligence, Databases, Software Engineering, etc.

 As a combination of different fields of Artificial Intelligence, the area of Knowledge-Based Systems applies knowledge representation, case-based reasoning, neural networks, Semantic Web and TICs used in different domains.

 The book offers a valuable resource for PhD students, Master’s and undergraduate students of Information Technology (IT)-related degrees such as Computer Science, Information Systems and Electronic Engineering.

This book presents innovative and high-quality research regarding advanced decision support systems (DSSs). It describes the foundations, methods, methodologies, models, tools, and techniques for designing, developing, implementing and evaluating advanced DSSs in different fields, including finance, health, emergency management, industry and pollution control. Decision support systems employ artificial intelligence methods to heuristically address problems that are cannot be solved using formal techniques. In this context, technologies such as the Semantic Web, linked data, big data, and machine learning are being applied to provide integrated support for individuals and organizations to make more rational decisions.

The book is organized into two parts. The first part covers decision support systems for industry, while the second part presents case studies related to clinical emergency management and pollution control.