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Dr. Jay Liebowitz Orkand Endowed Chair in Management and Technology University of Maryland University College Graduate School of Management & Technology 3501 University Boulevard East Adelphi, Maryland 20783-8030 USA jliebowitz@umuc. edu When I first heard the general topic of this book, Marketing Intelligent Systems or what I’ll refer to as Marketing Intelligence, it sounded quite intriguing. Certainly, the marketing field is laden with numeric and symbolic data, ripe for various types of mining—data, text, multimedia, and web mining. It’s an open laboratory for applying numerous forms of intelligentsia—neural networks, data mining, expert systems, intelligent agents, genetic algori...
Poor data quality is known to compromise the credibility and efficiency of commercial and public endeavours. Also, the importance of managing data quality has increased manifold as the diversity of sources, formats and volume of data grows. This volume targets the data quality in the light of collaborative information systems where data creation and ownership is increasingly difficult to establish.
"This book is to provide comprehensive coverage and understanding of various enterprise information systems (EIS) such as enterprise resource planning (ERP) and electronic commerce (EC) and their implications on supply chain management and organizational competitiveness"--Provided by publisher.
Evolutionary scheduling is a vital research domain at the interface of artificial intelligence and operational research. This edited book gives an overview of many of the current developments in the large and growing field of evolutionary scheduling. It demonstrates the applicability of evolutionary computational techniques to solve scheduling problems, not only to small-scale test problems, but also fully-fledged real-world problems.
Researchers and practitioners interested in the current De- cision Support System (DSS) and the shape of future DSS are the intended audience of this book. There is a particular, recurring emphasis on the adaptation of artificial intelli- gence techniques for use in the DSS world. The chapters are organized in two major sections, the first dealing with the- oretical topics and the second with applications.
As the most comprehensive reference work dealing with decision support systems (DSS), this book is essential for the library of every DSS practitioner, researcher, and educator. Written by an international array of DSS luminaries, it contains more than 70 chapters that approach decision support systems from a wide variety of perspectives. These range from classic foundations to cutting-edge thought, informative to provocative, theoretical to practical, historical to futuristic, human to technological, and operational to strategic. The chapters are conveniently organized into ten major sections that novices and experts alike will refer to for years to come.
Decision support systems have experienced a marked increase in attention and importance over the past 25 years. The aim of this book is to survey the decision support system (DSS) field – covering both developed territory and emergent frontiers. It will give the reader a clear understanding of fundamental DSS concepts, methods, technologies, trends, and issues. It will serve as a basic reference work for DSS research, practice, and instruction. To achieve these goals, the book has been designed according to a ten-part structure, divided in two volumes with chapters authored by well-known, well-versed scholars and practitioners from the DSS community.