Meant for those in government agencies, practicing managers, and academicians, this volume details how data mining can be used at various levels of management. Syvajarvi (administrative science, Lapla
Computer scientists from around the world report recent developments in data warehousing, focusing not on the static storage of data, but on how the data can be used to devise or refine business strat
Ultimately the large volumes of data that reside in or move through the electronic dimension of information must be presented for human consideration in some manner of simple visual form--chart, diagr
It's a research discipline in the throes of growth because of the quantity of data that can be assembled and the need to make sense of it. Effective mining of huge amounts of complex data requires a f
This work reviews practical and theoretical aspects of sensor network data management, for those working in database, data warehousing, data mining, and sensor network research. Chapters by internatio
International contributors present new developments in the areas of data warehousing and data mining. An introduction gives an overview of data warehousing and its importance in providing support for
The 13 chapters in this collection survey current work in storing and analyzing data and using algorithms to search and discover new knowledge automatically from multidimensional data sets. Several co
Technical, business, and political fields are represented, as well as Europe, Asia, Africa, and the Americas, in discussions of how advanced computer management of information by governments impacts u
Computer scientists describe the current state and trends in big data analytics, its technologies, and applications. Among their topics are a brief review on deep learning and types of implementati
For readers who may not be statisticians or data analysts, Sarmento and Costa explain how to analyze data using the Python and R languages. They have particularly in mind, students and researchers
This collection of fifteen articles on advanced data mining technologies provides an overview of current scholarship in this increasingly important field of information management. Divided into sectio
Fifteen articles on the theory and application of adaptive database search and retrieval technologies showcase current research in the growing field of machine learning algorithms. Divided into sectio
This book demonstrates the possibility of transforming machine learning algorithms into integrated commonsense reasoning processes in which inductive and deductive inferences correlate and support one
Web usage mining is the application of data mining technologies to discover interesting usage patterns from web data in order to understand and better serve the needs of web-based applications. The bu
Data analysis forms the basis of many forms of research ranging from the scientific to the governmental. With the advent of machine intelligence and neural networks, extracting, modeling, and approach
Intended to bridge the gap between the database and machine learning communities, this guide gathers theoretical and experimental contributions on fuzziness, scalability, and the use of fuzzy methods
Converting today's onslaught of information into usable knowledge is one of the main challenges facing us in the modern era. This volume covers a wide range of topics, from ontology learning to data m
Computer scientists describe the current understanding and practice of machine learning, both supervised and unsupervised, in a range of fields. They cover mobile vision for a plant biometric syste
Ontologies and formal representations of knowledge are extremely powerful tools for modeling and managing large applications in several domains ranging from knowledge engineering, to data mining, to
The 22 papers in this collection explore simulation theory, Petri nets, Monte Carlo, visualization, real-time simulation, and applications to neural networks, data mining, wireless networks, banks, an
