The chapters cover what instructors want students to know about MIS. Extended Learning Modules (XLM) show students what they can do with MIS. The instructor controls the mix by picking the chapters and XLMs to cover. A contemporary writing style and a wealth of examples engage students like no other MIS text.

An important work on a new framework for information retrieval: implications for artificial intelligence, natural language processing.

Class-tested and coherent, this textbook teaches classical and web information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. It gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students in computer science. Based on feedback from extensive classroom experience, the book has been carefully structured in order to make teaching more natural and effective. Slides and additional exercises (with solutions for lecturers) are also available through the book's supporting website to help course instructors prepare their lectures.

This book provides the most current and comprehensive overview available today of the critical role of information systems in emergency response and preparedness. It includes contributions from leading scholars, practitioners, and industry researchers, and covers all phases of disaster management - mitigation, preparedness, response, and recovery. 'Foundational' chapters provide a design framework and review ethical issues. 'Context' chapters describe the characteristics of individuals and organizations in which EMIS are designed and studied. 'Case Study' chapters include systems for distributed microbiology laboratory diagnostics to detect possible epidemics or bioterrorism, humanitarian MIS, and response coordination systems. 'Systems Design and Technology' chapters cover simulation, geocollaborative systems, global disaster impact analysis, and environmental risk analysis. Throughout the book, the editors and contributors give special emphasis to the importance of assessing the practical usefulness of new information systems for supporting emergency preparedness and response, rather than drawing conclusions from a theoretical understanding of the potential benefits of new technologies.

Information systems development is not merely a technical intervention but involves social and ethical dilemmas that affect the human, social and organizational domains. To demonstrate this point, the authors conduct a thorough and substantive description and analysis of the conceptual and philosophical underpinnings of systems development. In particular they analyse a number of systems development methodologies including structured methods, prototyping, ETHICS and Soft Systems Methodology to reveal the underlying conceptual and philosophical foundations. The book provides an in-depth analysis of data modelling theory and its links with theories of language and cognition. It offers a framework to describe and analyse different systems development approaches and to explain their strengths and weaknesses. The book is aimed at graduate students taking courses in information systems and data modelling, but will also appeal to information systems managers and professionals for whom the summary of methodologies will be useful.

A leading expert on the global software industry reveals the inner working of software giants like IBM, Microsoft, and Netscape, and shows what it takes to create, develop, and manage a successful company--in good times and bad--in the most fiercely competitive business in the world.

Experts investigate the reasons for low female participation in computing and suggest strategies for moving toward parity through studies of middle and high school girls, female students and postsecondary computer science programs, and women in the information technology workforce.

Data mining is the process of extracting hidden patterns from data, and it’s commonly used in business, bioinformatics, counter-terrorism, and, increasingly, in professional sports. First popularized in Michael Lewis’ best-selling Moneyball: The Art of Winning An Unfair Game, it is has become an intrinsic part of all professional sports the world over, from baseball to cricket to soccer. While an industry has developed based on statistical analysis services for any given sport, or even for betting behavior analysis on these sports, no research-level book has considered the subject in any detail until now. Sports Data Mining brings together in one place the state of the art as it concerns an international array of sports: baseball, football, basketball, soccer, greyhound racing are all covered, and the authors (including Hsinchun Chen, one of the most esteemed and well-known experts in data mining in the world) present the latest research, developments, software available, and applications for each sport. They even examine the hidden patterns in gaming and wagering, along with the most common systems for wager analysis.