Developing Multi-Database Mining Applications PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Developing Multi-Database Mining Applications PDF full book. Access full book title Developing Multi-Database Mining Applications by Animesh Adhikari. Download full books in PDF and EPUB format.
Author: Animesh Adhikari
Publisher: Springer Science & Business Media
ISBN: 1849960445
Category : Computers
Languages : en
Pages : 134
Get Book Here
Book Description
Multi-database mining has been recognized recently as an important and strategically essential area of research in data mining. In this book, we discuss various issues regarding the systematic and efficient development of multi-database mining applications. It explains how systematically one could prepare data warehouses at different branches. As appropriate multi-database mining technique is essential to develop better applications. Also, the efficiency of a multi-database mining application could be improved by processing more patterns in the application. A faster algorithm could also play an important role in developing a better application. Thus the efficiency of a multi-database mining application could be enhanced by choosing an appropriate multi-database mining model, an appropriate pattern synthesizing technique, a better pattern representation technique, and an efficient algorithm for solving the problem. This book illustrates each of these issues either in the context of a specific problem, or in general.
Author: Animesh Adhikari
Publisher: Springer Science & Business Media
ISBN: 1849960445
Category : Computers
Languages : en
Pages : 134
Get Book Here
Book Description
Multi-database mining has been recognized recently as an important and strategically essential area of research in data mining. In this book, we discuss various issues regarding the systematic and efficient development of multi-database mining applications. It explains how systematically one could prepare data warehouses at different branches. As appropriate multi-database mining technique is essential to develop better applications. Also, the efficiency of a multi-database mining application could be improved by processing more patterns in the application. A faster algorithm could also play an important role in developing a better application. Thus the efficiency of a multi-database mining application could be enhanced by choosing an appropriate multi-database mining model, an appropriate pattern synthesizing technique, a better pattern representation technique, and an efficient algorithm for solving the problem. This book illustrates each of these issues either in the context of a specific problem, or in general.
Author: Rahman, Hakikur
Publisher: IGI Global
ISBN: 1599046598
Category : Technology & Engineering
Languages : en
Pages : 356
Get Book Here
Book Description
Presents an overview of the main issues of data mining, including its classification, regression, clustering, and ethical issues. Provides readers with knowledge enhancing processes as well as a wide spectrum of data mining applications.
Author: Ken Yale
Publisher: Elsevier
ISBN: 0124166458
Category : Mathematics
Languages : en
Pages : 824
Get Book Here
Book Description
Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application. This book is an ideal reference for users who want to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques and discusses their application to real problems in ways accessible and beneficial to practitioners across several areas—from science and engineering, to medicine, academia and commerce. - Includes input by practitioners for practitioners - Includes tutorials in numerous fields of study that provide step-by-step instruction on how to use supplied tools to build models - Contains practical advice from successful real-world implementations - Brings together, in a single resource, all the information a beginner needs to understand the tools and issues in data mining to build successful data mining solutions - Features clear, intuitive explanations of novel analytical tools and techniques, and their practical applications
Author: Xindong Wu
Publisher:
ISBN: 9783662174012
Category :
Languages : en
Pages : 452
Get Book Here
Book Description
Author: Shichao Zhang
Publisher: Springer Science & Business Media
ISBN: 0857293885
Category : Computers
Languages : en
Pages : 237
Get Book Here
Book Description
Many organizations have an urgent need of mining their multiple databases inherently distributed in branches (distributed data). In particular, as the Web is rapidly becoming an information flood, individuals and organizations can take into account low-cost information and knowledge on the Internet when making decisions. How to efficiently identify quality knowledge from different data sources has become a significant challenge. This challenge has attracted a great many researchers including the au thors who have developed a local pattern analysis, a new strategy for dis covering some kinds of potentially useful patterns that cannot be mined in traditional multi-database mining techniques. Local pattern analysis deliv ers high-performance pattern discovery from multiple databases. There has been considerable progress made on multi-database mining in such areas as hierarchical meta-learning, collective mining, database classification, and pe culiarity discovery. While these techniques continue to be future topics of interest concerning multi-database mining, this book focuses on these inter esting issues under the framework of local pattern analysis. The book is intended for researchers and students in data mining, dis tributed data analysis, machine learning, and anyone else who is interested in multi-database mining. It is also appropriate for use as a text supplement for broader courses that might also involve knowledge discovery in databases and data mining.
Author: Zheng, Robert Z.
Publisher: IGI Global
ISBN: 1799802515
Category : Education
Languages : en
Pages : 393
Get Book Here
Book Description
Multiple intelligences (MI) as a cognitive psychology theory has significantly influenced learning and teaching. Research has demonstrated a strong association between individual intelligences and their cognitive processes and behaviors. However, it remains unknown how each of or a combination of these intelligences can be effectively optimized through instructional intervention, particularly through the use of emerging learning technology. On the other hand, while efforts have been made to unveil the relationship between information and communication technology (ICT) and individual learner performance, there is a lack of knowledge in how MI theory may guide the use of ICTs to enhance learning opportunities for students. Examining Multiple Intelligences and Digital Technologies for Enhanced Learning Opportunities is an essential reference book that generates new knowledge about how ICTs can be utilized to promote MI in various formal and informal learning settings. Featuring a range of topics such as augmented reality, learning analytics, and mobile learning, this book is ideal for teachers, instructional designers, curriculum developers, ICT specialists, educational professionals, administrators, instructors, academicians, and researchers.
Author: Kazumi Nakamatsu
Publisher: World Scientific
ISBN: 9814489166
Category : Computers
Languages : en
Pages : 680
Get Book Here
Book Description
This book consists of various contributions in conjunction with the keywords “reasoning” and “intelligent systems”, which widely covers theoretical to practical aspects of intelligent systems. Therefore, it is suitable for researchers or graduate students who want to study intelligent systems generally.
Author: Sugumaran, Vijayan
Publisher: IGI Global
ISBN: 1599049422
Category : Computers
Languages : en
Pages : 2469
Get Book Here
Book Description
This set compiles more than 240 chapters from the world's leading experts to provide a foundational body of research to drive further evolution and innovation of these next-generation technologies and their applications, of which scientific, technological, and commercial communities have only begun to scratch the surface.
Author: Vijayan Sugumaran
Publisher: Springer Nature
ISBN: 3030748146
Category : Technology & Engineering
Languages : en
Pages : 970
Get Book Here
Book Description
This book provides comprehensive coverage of the latest advances and trends in information technology, science and engineering. Specifically, it addresses a number of broad themes, including multi-modal informatics, data mining, agent-based and multi-agent systems for health and education informatics, which inspire the development of intelligent information technologies. The contributions cover a wide range of topics such as AI applications and innovations in health and education informatics; data and knowledge management; multi-modal application management; and web/social media mining for multi-modal informatics. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals, and a useful reference guide for newcomers to the field. This book is a compilation of the papers presented in the 2021 International Conference on Multi-modal Information Analytics, held in Huhehaote, China, on April 23–24, 2021.
Author: Animesh Adhikari
Publisher: Springer Science & Business Media
ISBN: 3319034103
Category : Technology & Engineering
Languages : en
Pages : 247
Get Book Here
Book Description
Pattern recognition in data is a well known classical problem that falls under the ambit of data analysis. As we need to handle different data, the nature of patterns, their recognition and the types of data analyses are bound to change. Since the number of data collection channels increases in the recent time and becomes more diversified, many real-world data mining tasks can easily acquire multiple databases from various sources. In these cases, data mining becomes more challenging for several essential reasons. We may encounter sensitive data originating from different sources - those cannot be amalgamated. Even if we are allowed to place different data together, we are certainly not able to analyze them when local identities of patterns are required to be retained. Thus, pattern recognition in multiple databases gives rise to a suite of new, challenging problems different from those encountered before. Association rule mining, global pattern discovery and mining patterns of select items provide different patterns discovery techniques in multiple data sources. Some interesting item-based data analyses are also covered in this book. Interesting patterns, such as exceptional patterns, icebergs and periodic patterns have been recently reported. The book presents a thorough influence analysis between items in time-stamped databases. The recent research on mining multiple related databases is covered while some previous contributions to the area are highlighted and contrasted with the most recent developments.
