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The 8th International Database Workshop, organized by the Hong Kong Computer Society and held in Hong Kong in July 1997, dedicated its theme to Data Mining, Data Warehouse and Client/Server Databases with separate focuses on the Academic and the Industrial Streams. It brought together database practitioners, researchers and vendors to share and explore their methodologies and experiences of advance database systems. These proceedings contain 22 of the selected papers received for the section on the Industrial Stream, written by database vendors and consultants from 14 countries around the world. It will serve as a useful and practical technology reference book on the latest findings in the field.
The 8th International Database Workshop, organized by the Hong Kong Computer Society and held in Hong Kong in July 1997, dedicated its theme to Data Mining, Data Warehouse and Client/Server Databases with separate focuses on the Academic and the Industrial Streams. It brought together database practitioners, researchers and vendors to share and explore their methodologies and experiences of advance database systems. . These proceedings contain 21 of the selected papers received for the section on the Academic Stream, written by database practitioners and researchers from 13 countries around the world. It will serve as a useful and practical technology reference book on the latest findings in the field.
Mining Very Large Databases with Parallel Processing addresses the problem of large-scale data mining. It is an interdisciplinary text, describing advances in the integration of three computer science areas, namely `intelligent' (machine learning-based) data mining techniques, relational databases and parallel processing. The basic idea is to use concepts and techniques of the latter two areas - particularly parallel processing - to speed up and scale up data mining algorithms. The book is divided into three parts. The first part presents a comprehensive review of intelligent data mining techniques such as rule induction, instance-based learning, neural networks and genetic algorithms. Likewise, the second part presents a comprehensive review of parallel processing and parallel databases. Each of these parts includes an overview of commercially-available, state-of-the-art tools. The third part deals with the application of parallel processing to data mining. The emphasis is on finding generic, cost-effective solutions for realistic data volumes. Two parallel computational environments are discussed, the first excluding the use of commercial-strength DBMS, and the second using parallel DBMS servers. It is assumed that the reader has a knowledge roughly equivalent to a first degree (BSc) in accurate sciences, so that (s)he is reasonably familiar with basic concepts of statistics and computer science. The primary audience for Mining Very Large Databases with Parallel Processing is industry data miners and practitioners in general, who would like to apply intelligent data mining techniques to large amounts of data. The book will also be of interest to academic researchers and postgraduate students, particularly database researchers, interested in advanced, intelligent database applications, and artificial intelligence researchers interested in industrial, real-world applications of machine learning.
There is now so much data on the Web that managing it with conventional tools is becoming almost impossible. To manage this data, provide interoperability and warehousing between multiple data sources and systems, and extract information from the databases and warehouses, various tools are being developed. In fact, developments in multimedia database management have exploded during the past decade. To date, however, there has been little information available on providing a complete set of services for multimedia databases, including their management, mining, and integration on the Web for electronic enterprises. Managing and Mining Multimedia Databases fills that gap. Focusing on managing and mining multimedia databases for electronic commerce and business, it explores database management system techniques for text, image, audio, and video databases. It addresses the issues and challenges of mining multimedia databases to extract information, and discusses the directions and challenges related to integrating multimedia databases for the Web, particularly for e-business. This book provides a comprehensive overview of multimedia data management and mining technologies, from the underlying concepts, architectures, and data models for multimedia database systems to the technologies that support multimedia data management on the Web, privacy issues, and emerging standards, prototypes, and products. Designed for technical managers, executives, and technologists, it offers your only opportunity to learn about both multimedia data management and multimedia data mining within a single book.
The data warehousing bible updated for the new millennium Updated and expanded to reflect the many technological advances occurring since the previous edition, this latest edition of the data warehousing "bible" provides a comprehensive introduction to building data marts, operational data stores, the Corporate Information Factory, exploration warehouses, and Web-enabled warehouses. Written by the father of the data warehouse concept, the book also reviews the unique requirements for supporting e-business and explores various ways in which the traditional data warehouse can be integrated with new technologies to provide enhanced customer service, sales, and support-both online and offline-including near-line data storage techniques.
Focusing on three applications of data mining, Design and Implementation of Data Mining Tools explains how to create and employ systems and tools for intrusion detection, Web page surfing prediction, and image classification. Mainly based on the authors' own research work, the book takes a practical approach to the subject.The first part of the boo
The explosion of Web-based data has created a demand among executives and technologists for methods to identify, gather, analyze, and utilize data that may be of value to corporations and organizations. The emergence of data mining, and the larger field of Web mining, has businesses lost within a confusing maze of mechanisms and strategies for obta
This revised and updated book, now in its Second Edition, continues to provide excellent coverage of the basic concepts involved in database management systems. It provides a thorough treatment of some important topics such as data structure, data models and database design through presentation of well-defined algorithms, examples and real-life cases. There is also detailed coverage of data definition and data manipulation parts of IMS and PC-FOCUS—the two popular database management systems—to access and manipulate hierarchical database, besides IDMS (Network) and Interactive SQL (Relational) database languages, using suitable programs based on case studies. WHAT IS NEW TO THIS EDITION : Includes five new chapters, namely, Distributed Database Management System, Client/Server Systems, Data Warehousing, Data Mining, and Object Oriented Database Management System (OODBMS) to cover the modern concepts of DBMS. Provides a new section on cryptography for network security. The textbook is primarily designed for the postgraduate students of management, computer science and information technology. It should also serve as a useful text for B.E./B.Tech. students in computer science engineering and software engineering. Besides students, this book will also be useful for computer professionals engaged in design, operation and maintenance of database.