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This volume presents methods for the analysis of quantitative and qualitative data, and for the processing and ordering of symbolic or linguistic information. The 45 papers combine methods from exploratory and inferential statistics with mathematical and numerical approaches, investigate conceptual classification and ordering structures and describe recent developments for knowledge-based information systems. The contributions are grouped into seven chapters: 1. Classification and Clustering, 2. Uncertainty and Fuzziness, 3. Methods of Data Analysis and Applications, 4. Statistical Models and Methods, 5. Bayesian Learning, 6. Conceptual Classification, Knowledge Ordering and Information Systems, 7. Linguistics and Dialectometry.
Information systems belong to the most complex artifacts built in today's society. Developing, maintaining, and using an information system raises a large number of difficult problems, ranging from purely technical to organizational and social. Information Systems Engineering: From Data Analysis to Process Networks presents the most current research on existing and emergent trends on conceptual modeling and information systems engineering, bridging the gap between research and practice by providing a much-needed reference point on the design of software systems that evolve seamlessly to adapt to rapidly changing business and organizational practices.
This book offers postgraduate and early career researchers in accounting and information systems a guide to choosing, executing and reporting appropriate data analysis methods to answer their research questions. It provides readers with a basic understanding of the steps that each method involves, and of the facets of the analysis that require special attention. Rather than presenting an exhaustive overview of the methods or explaining them in detail, the book serves as a starting point for developing data analysis skills: it provides hands-on guidelines for conducting the most common analyses and reporting results, and includes pointers to more extensive resources. Comprehensive yet succinct, the book is brief and written in a language that everyone can understand - from students to those employed by organizations wanting to study the context in which they work. It also serves as a refresher for researchers who have learned data analysis techniques previously but who need a reminder for the specific study they are involved in.
In any software design project, the analysis of stage documenting and designing of technical requirements for the needs of users is vital to the success of the project. This book provides a thorough introduction and survey on all aspects of analysis, including design of E-commerce systems, and how it fits into the software engineering process. The material is based on successful professional courses offered at Columbia University to a diverse audience of advanced students and professionals. An emphasis is placed on the stages of analysis and the presentation of many alternative modeling tools that an analyst can utilise. Particular attention is paid to interviews, modeling tools, and approaches used in building effective web-based E-commerce systems.
Data Analytics for Intelligent Transportation Systems provides in-depth coverage of data-enabled methods for analyzing intelligent transportation systems (ITS), including the tools needed to implement these methods using big data analytics and other computing techniques. The book examines the major characteristics of connected transportation systems, along with the fundamental concepts of how to analyze the data they produce. It explores collecting, archiving, processing, and distributing the data, designing data infrastructures, data management and delivery systems, and the required hardware and software technologies. It presents extensive coverage of existing and forthcoming intelligent transportation systems and data analytics technologies. All fundamentals/concepts presented in this book are explained in the context of ITS. Users will learn everything from the basics of different ITS data types and characteristics to how to evaluate alternative data analytics for different ITS applications. They will discover how to design effective data visualizations, tactics on the planning process, and how to evaluate alternative data analytics for different connected transportation applications, along with key safety and environmental applications for both commercial and passenger vehicles, data privacy and security issues, and the role of social media data in traffic planning. Data Analytics for Intelligent Transportation Systems will prepare an educated ITS workforce and tool builders to make the vision for safe, reliable, and environmentally sustainable intelligent transportation systems a reality. It serves as a primary or supplemental textbook for upper-level undergraduate and graduate ITS courses and a valuable reference for ITS practitioners. - Utilizes real ITS examples to facilitate a quicker grasp of materials presented - Contains contributors from both leading academic and commercial domains - Explains how to design effective data visualizations, tactics on the planning process, and how to evaluate alternative data analytics for different connected transportation applications - Includes exercise problems in each chapter to help readers apply and master the learned fundamentals, concepts, and techniques - New to the second edition: Two new chapters on Quantum Computing in Data Analytics and Society and Environment in ITS Data Analytics
Most of modern enterprises, institutions, and organizations rely on knowledge-based management systems. In these systems, knowledge is gained from data analysis. Today, knowledge-based management systems include data warehouses as their core components. Data integrated in a data warehouse are analyzed by the so-called On-Line Analytical Processing (OLAP) applications designed to discover trends, patterns of behavior, and anomalies as well as finding dependencies between data. Massive amounts of integrated data and the complexity of integrated data coming from many different sources make data integration and processing challenging. New Trends in Data Warehousing and Data Analysis brings together the most recent research and practical achievements in the DW and OLAP technologies. It provides an up-to-date bibliography of published works and the resource of research achievements. Finally, the book assists in the dissemination of knowledge in the field of advanced DW and OLAP.
Proceedings of the 17th Annual Conference of the Gesellschaft für Klassifikation e.V., University of Kaiserslautern, March 3 - 5, 1993
"Information Systems Analysis and Design presents essential knowledge about management information systems development. It is used for four-year university/college students who study information systems analysis and design. Students will learn the information systems development strategies and the process of information systems development. The book emphasizes the key methods of information systems acquisition development, including business process modeling and systems acquisition design. To maintain a well-rounded approach to the topic, both fundamental knowledge about information systems development and hands-on materials are presented. Succinct tutorials for professional systems development project are also included"--
Research Methods: Information, Systems, and Contexts, Second Edition, presents up-to-date guidance on how to teach research methods to graduate students and professionals working in information management, information science, librarianship, archives, and records and information systems. It provides a coherent and precise account of current research themes and structures, giving students guidance, appreciation of the scope of research paradigms, and the consequences of specific courses of action. Each of these valuable sections will help users determine the relevance of particular approaches to their own questions. The book presents academics who teach research and information professionals who carry out research with new resources and guidance on lesser-known research paradigms. - Provides up-to-date knowledge of research methods and their applications - Provides a coherent and precise account of current research themes and structures through chapters written by authors who are experts in their fields - Helps students and researchers understand the range of quantitative and qualitative approaches available for research, as well as how to make practical use of them - Provides many illustrations from projects in which authors have been involved, to enhance understanding - Emphasises the nexus between formulation of research question and choice of research methodology - Enables new researchers to understand the implications of their planning decisions
In businesses and organizations, understanding the social reality of individuals, groups, and cultures allows for in-depth understanding and rich analysis of multiple research areas to improve practices. Qualitative research provides important insight into the interactions of the workplace. Qualitative Techniques for Workplace Data Analysis is an essential reference source that discusses the qualitative methods used to analyze workplace data, as well as what measures should be adopted to ensure the credibility and dependability of qualitative findings in the workplace. Featuring research on topics such as collection methods, content analysis, and sampling, this book is ideally designed for academicians, development practitioners, business managers, and analytic professionals seeking coverage on quality measurement techniques in the occupational settings of emerging markets.