E-commerce has passed through a number of stages in the minds of most readers of the daily press. Initially it was the province of the specialist and considered almost irrelevant to the needs and activities of everyday life - companies looking for venture capital in this area had little if any chance of obtaining sufficient funds from the rather conservative investors who provided the only source of start-up capital. Then came the dot. com boom -and suddenly e-commerce was the most exciting topic possible! Venture capital was available from every possible source and almost any company with a . com in its name could be assured of instant funding on request. This boom was, inevitably, followed by the dot. com bust and the press wamed that the days of e-commerce were gone, perhaps never to return. This apparently confusing 'stages of growth' model is in reality nothing ofthe sort. E-commerce is simply the logical outcome of combining computers with tele communications networks. The astonishing changes which a global economy has brought with it are reflected in the changes to the way we do business which are increasingly synonymous with e-commerce. Indeed, the term e-commerce itself is coming to mean only the transaction-based component of e-business-'any process that a business organisation conducts over a computer-mediated network' as Thomas Mesenbourg ofthe U. S. Census Bureau said in 1999.

As the Internet becomes increasingly interconnected with modern society, the transition to online business has developed into a prevalent form of commerce. While there exist various advantages and disadvantages to online business, it plays a major role in contemporary business methods. Improving E-Commerce Web Applications Through Business Intelligence Techniques provides emerging research on the core areas of e-commerce web applications. While highlighting the use of data mining, search engine optimization, and online marketing to advance online business, readers will learn how the role of online commerce is becoming more prevalent in modern business. This book is an important resource for vendors, website developers, online customers, and scholars seeking current research on the development and use of e-commerce.

This book covers significant recent developments in the field of Intelligent Meth ods applied to eCommerce. The Intelligent Methods considered are mainly Soft Computing Methods that include fuzzy sets, rough sets, neural networks, evolutionary computations, probabilistic and evidential reasoning, multivalued logic, and related fields. There is not doubt about the relevance of eCommerce in our daily environ ments and in the work carried out at many research centers throughout the world. The application of AI to Commerce is growing as fast as the computers and net works are being integrated in all business and commerce aspects. We felt that it was time to sit down and see how was the impact into that field of low-level AI, i.e. softcomputing. We found many scattered contributions disseminated in con ferences, workshops, journal, books or even technical reports, but nothing like a common framework that could serve as a basis for further research, comparison or even prototyping for a direct transfer to the industry. We felt then the need to set up a reference point, a book like this. We planned this book as a recompilation of the newest developments of re searchers who already made some contribution into the field. The authors were se lected based on the originality and quality of their work and its relevance to the field. Authors came from prestigious universities and research centers with differ ent backgrounds.

Sustainable supply chain management involves integrating environmentally and financially viable practices into the complete supply chain lifecycle, from product design and development to material selection and sourcing, manufacturing, packaging, transportation, and distribution. A sustainable supply chain ensures balance between economic, social, and environmental performances – such as better assurance of human rights, ethical work practices, carbon footprint reduction, waste management, and resource efficiency. Computational Intelligence Techniques for Sustainable Supply Chain Management presents state-of-the-art computational intelligence techniques and applications for supply chain sustainability issues and logistic problems, filling the gap between general textbooks on sustainable supply chain management and more specialized literature dealing with methods for computational intelligence. This book focuses on addressing problems in advanced topics in the sustainable supply chain, and will appeal to practitioners, managers, researchers, academicians, students, and professionals interested in sustainable logistics, sustainable procurement, sustainable manufacturing, sustainable inventory and production management, sustainable scheduling, sustainable transportation, and sustainable network design. - Serves as a reference on computational intelligence–enabled sustainable supply chains for graduate students in computer/data science, industrial engineering, industrial ecology, and business - Explores key topics in sustainable supply chain informatics, that is, heuristics, metaheuristics, robotics, simulation, machine learning, big data analytics and artificial intelligence - Provides a foundation for industry leaders and professionals to understand recent and cutting-edge methodologies and technologies in the domain of sustainable supply chain powered by computational intelligence techniques

This book presents recently developed intelligent techniques with applications and theory in the area of engineering management. The involved applications of intelligent techniques such as neural networks, fuzzy sets, Tabu search, genetic algorithms, etc. will be useful for engineering managers, postgraduate students, researchers, and lecturers. The book has been written considering the contents of a classical engineering management book but intelligent techniques are used for handling the engineering management problem areas. This comprehensive characteristics of the book makes it an excellent reference for the solution of complex problems of engineering management. The authors of the chapters are well-known researchers with their previous works in the area of engineering management.

The book aims at presenting a multidisciplinary view meant to illustrate several significant efforts and results about the contribution of information technologies to make available new resources and enable rationally usage the existing ones in the context of the ever-growing trends to use ever more resources. Authors from various countries have been invited to contribute so that a rather broad and balanced image about the current trends and recent results obtained could result. The proposed book addresses methodologies and information technology-based tools and systems designed for the efficient use of diverse resources such as manpower and human knowledge, natural resources including water, raw materials and end of life products, financial assets, datasets, and even cultural goods. The book is organized in ten chapters. It is intended to be insightful for researchers, instructors, and planers from various domains. It can also be used as an auxiliary material for postgraduate studies in applied informatics, business administration, industrial engineering, engineering and management, computer, and digital humanities.

Although recommendation systems have become a vital research area in the fields of cognitive science, approximation theory, information retrieval and management sciences, they still require improvements to make recommendation methods more effective and intelligent. Intelligent Techniques in Recommendation Systems: Contextual Advancements and New Methods is a comprehensive collection of research on the latest advancements of intelligence techniques and their application to recommendation systems and how this could improve this field of study.

This book constitutes the thoroughly refereed post-proceedings of the Second Workshop on Intelligent Techniques in Web Personalization, ITWP 2003, held in Acapulco, Mexico in August 2003 as part of IJCAI 2003, the 18th International Joint Conference on Artificial Intelligence. The 17 revised full papers presented were carefully selected and include extended versions of some of the papers presented at the ITWP 2003 workshop as well as a number of invited chapters by leading researchers in the field of Intelligent Techniques for Web Personalization. The papers are organized in topical sections on user modelling, recommender systems, enabling technologies, personalized information access, and systems and applications.

Software is an integral part of our lives today. Modern software systems are highly complex and often pose new challenges in different aspects of Software Engineering (SE).Artificial Intelligence (AI) is a growing field in computer science that has been proven effective in applying and developing AI techniques to address various SE challenges.This unique compendium covers applications of state-of-the-art AI techniques to the key areas of SE (design, development, debugging, testing, etc).All the materials presented are up-to-date. This reference text will benefit researchers, academics, professionals, and postgraduate students in AI, machine learning and software engineering.Related Link(s)

Artificial Intelligence Techniques in IoT Sensor Networks is a technical book which can be read by researchers, academicians, students and professionals interested in artificial intelligence (AI), sensor networks and Internet of Things (IoT). This book is intended to develop a shared understanding of applications of AI techniques in the present and near term. The book maps the technical impacts of AI technologies, applications and their implications on the design of solutions for sensor networks. This text introduces researchers and aspiring academicians to the latest developments and trends in AI applications for sensor networks in a clear and well-organized manner. It is mainly useful for research scholars in sensor networks and AI techniques. In addition, professionals and practitioners working on the design of real-time applications for sensor networks may benefit directly from this book. Moreover, graduate and master’s students of any departments related to AI, IoT and sensor networks can find this book fascinating for developing expert systems or real-time applications. This book is written in a simple and easy language, discussing the fundamentals, which relieves the requirement of having early backgrounds in the field. From this expectation and experience, many libraries will be interested in owning copies of this work.